Detecting colorectal neoplasm

ABSTRACT

Provided herein is technology relating to detecting neoplasia and particularly, but not exclusively, to methods, compositions, and related uses for detecting premalignant and malignant neoplasms such as colorectal cancer.

FIELD OF INVENTION

Provided herein is technology relating to detecting neoplasia andparticularly, but not exclusively, to methods, compositions, and relateduses for detecting premalignant and malignant neoplasms such ascolorectal cancer.

BACKGROUND

Colorectal cancer remains the 2^(nd) most common cancer in U.S. men andwomen combined (Siegel R, et al., CA Cancer J Clin 2013; 63:11-30). Theunderlying biology of progression from precursor lesion to cancer lendsitself favorably to screening (Vogelstein B, et al., Science 2013;339:1546-58). Evidence supports and guidelines endorse any of severaltests and strategies (Levin B, et al., Gastroenterology 2008;134:1570-95; Rex D K, et al., Am J Gastroenterol 2009; 104:739-50; KarlJ, et al., Clin Gastroenterol Hepatol 2008; 6:1122-8). From a societalperspective, screening is considered cost-effective (Karl J, et al.,Clin Gastroenterol Hepatol 2008; 6:1122-8; Heitman S J, et al., PLoS Med2010; 7:e1000370; Parekh M, et al., Aliment Pharmacol Ther 2008;27:697-712; Sharaf R N, et al., Am J Gastroenterol 2013; 108:120-32).

Colorectal cancer arises from accumulated genetic and epigeneticalterations, providing a basis for analysis of stool for tumor-specificchanges (Berger B M, et al., Pathology 2012; 44:80-8). Previouslarge-scale studies of early generation stool-based DNA tests in thescreening setting demonstrated only fair sensitivity for colorectalcancer and low sensitivity for advanced adenomas (Ahlquist D A, et al.,Ann Intern Med 2008; 149:441-50, W81; Imperiale T F, et al., N Engl JMed 2004; 351:2704-14). Important advances have since been incorporated,including a stabilizing buffer (Boynton K A, et al., Clin Chem 2003;49:1058-65; Zou H, et al., Cancer Epidemiol Biomarkers Prev 2006;15:1115-9), more discriminant markers (Ahlquist D A, et al.,Gastroenterology 2012; 142:248-56; Bardan E, et al., Israel journal ofmedical sciences 1997; 33:777-80), platforms with higher analyticsensitivity (Ahlquist D A, et al., Gastroenterology 2012; 142:248-56;Aronchick C A, et al., Gastrointestinal endoscopy 2000; 52:346-52),result determination using a logistic regression analysis rather thanindividual marker values, and automation.

Although screening reduces colorectal cancer mortality (Mandel J S, etal., N Engl J Med. 1993, 328:1365-71; Hardcastle J D, et al., Lancet.1996, 348:1472-7; Kronborg O, et al., Scand J Gastroenterol. 2004,39:846-51; Winawer S J, et al., J Natl Cancer Inst. 1993, 85:1311-8;Singh H, et al., JAMA. 2006, 295:2366-73), observed reductions have beenmodest (Singh H, et al., JAMA. 2006; 295, 2366-73; Heresbach D, et al.,Eur J Gastroenterol Hepatol. 2006, 18:427-33) and more than one half ofadults in the United States have not received screening (Meissner H I,Cancer Epidemiol Biomarkers Prev. 2006, 15:389-94).

An emerging approach to cancer screening involves the assay oftumor-specific DNA alterations in bodily samples from cancer patients,such as stool, serum, and urine (Osborn N K, Ahlquist D A.Gastroenterology 2005; 128:192-206; Ahlquist D A, et al.,Gastroenterology 2000; 119:1219-27; Ahlquist D A, et al.,Gastroenterology 2002; 122:Suppl A40; Chen W D, et al., J Natl CancerInst 2005; 97:1124-32; Zou H, et al., Cancer Epidemiol Biomarkers Prev2006; 15:1115-9; Zou H Z, Clin Cancer Res 2002; 8:188-91; Hogue M O, JClin Oncol 2005; 23:6569-75; Belinsky S A, et al., Cancer Res 2006;66:3338-44; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007;5:111-7′ Kann L, et al., Clin Chem 2006; 52:2299-302). It is importantto select markers with high accuracy if efficiency and effectiveness areto be achieved in a cancer screening application. Due to the molecularheterogeneity of colorectal neoplasia, high detection rates oftenrequire a panel of markers.

Several methylated genes have been detected in the stool andserum/plasma samples from colorectal cancer patients (Ahlquist D A,Gastroenterology 2002; 122:Suppl A40; Chen W D, et al., J Natl CancerInst 2005; 97:1124-32; Zou H Z, et al., Clin Cancer Res 2002; 8:188-91;Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007; 5:111-7; PetkoZ, et al., Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet2004; 363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert MP, et al., Gastroenterology 2006; 131:1418-30; Grady W M, et al., CancerRes 2001; 61:900-2). Whereas some methylated genes have been found in amajority of colorectal cancers, the yield of bodily fluid-based assaysremains suboptimal (Ahlquist D A, et al., Gastroenterology 2002;122:Suppl A40; Chen W D, et al., J Natl Cancer Inst 2005; 97:1124-32;Zou H, et al., Cancer Epidemiol Biomarkers Prev 2006; 15:1115-9; Zou HZ, Clin Cancer Res 2002; 8:188-91; Belinsky S A, et al., Cancer Res2006; 66:3338-44; Itzkowitz S H, et al., Clin Gastroenterol Hepatol2007; 5:111-7; Kann L, et al., Clin Chem 2006; 52:2299-302; Petko Z, etal., Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet 2004;363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert M P, etal., Gastroenterology 2006; 131:1418-30; Grady W M, et al., Cancer Res2001; 61:900-2).

More accurate, user-friendly, and widely distributable tools to improvescreening effectiveness, acceptability, and access are needed.

SUMMARY

Methylated DNA has been studied as a potential class of biomarkers inthe tissues of most tumor types. In many instances, DNAmethyltransferases add a methyl group to DNA atcytosine-phosphate-guanine (CpG) island sites as an epigenetic controlof gene expression. In a biologically attractive mechanism, acquiredmethylation events in promoter regions of tumor suppressor genes arethought to silence expression, thus contributing to oncogenesis. DNAmethylation may be a more chemically and biologically stable diagnostictool than RNA or protein expression (Laird (2010) Nat Rev Genet 11:191-203). Furthermore, in cancers such as sporadic colon cancer,methylation markers offer excellent specificity and are more broadlyinformative and sensitive than are individual DNA mutations (Zou et al(2007) Cancer Epidemiol Biomarkers Prev 16: 2686-96).

Analysis of CpG islands has yielded important findings when applied toanimal models and human cell lines. For example, Zhang and colleaguesfound that amplicons from different parts of the same CpG island mayhave different levels of methylation (Zhang et al. (2009) PLoS Genet 5:e1000438). Further, methylation levels were distributed bi-modallybetween highly methylated and unmethylated sequences, further supportingthe binary switch-like pattern of DNA methyltransferase activity (Zhanget al. (2009) PLoS Genet 5: e1000438). Analysis of murine tissues invivo and cell lines in vitro demonstrated that only about 0.3% of highCpG density promoters (HCP, defined as having >7% CpG sequence within a300 base pair region) were methylated, whereas areas of low CpG density(LCP, defined as having <5% CpG sequence within a 300 base pair region)tended to be frequently methylated in a dynamic tissue-specific pattern(Meissner et al. (2008) Nature 454: 766-70). HCPs include promoters forubiquitous housekeeping genes and highly regulated developmental genes.Among the HCP sites methylated at >50% were several established markerssuch as Wnt 2, NDRG2, SFRP2, and BMP3 (Meissner et al. (2008) Nature454: 766-70).

Methylated genes have been detected in the blood and stool of patientswith colorectal cancer and proposed as candidate screening markers(Ahlquist D A, et al., Gastroenterology 2002; 122:Suppl A40; Chen W D,et al., J Natl Cancer Inst 2005; 97:1124-32; Zou H Z, Clin Cancer Res2002; 8:188-91; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007;5:111-7; Kann L, et al., Clin Chem 2006; 52:2299-302; Petko Z, et al.,Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet 2004;363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert M P, etal., Gastroenterology 2006; 131:1418-30; Grady W M, et al., Cancer Res2001; 61:900-2).

Zou and colleagues, for example, evaluated genes frequently methylatedin colorectal neoplasia to identify the most discriminant ones (Zou, etal., 2007 Cancer Epidemiol Biomarkers Prev. 16(12):2686-2696). Fourgenes specifically methylated in colorectal cancer (bone morphogeneticprotein 3 (BMP3), EYA2, aristaless-like homeobox-4 (ALX4), and vimentin)were selected from 41 candidate genes and evaluated on 74 cancers, 62adenomas, and 70 normal epithelia. Methylation status was analyzedqualitatively and quantitatively and confirmed by bisulfite genomicsequencing. Effect of methylation on gene expression was evaluated infive colon cancer cell lines. K-ras and BRAF mutations were detected bysequencing. Methylation of BMP3, EYA2, ALX4, or vimentin was detectedrespectively in 66%, 66%, 68%, and 72% of cancers; 74%, 48%, 89%, and84% of adenomas; and 7%, 5%, 11%, and 11% of normal epithelia (P<0.01,cancer or adenoma versus normal). It was concluded that BMP3, EYA2,ALX4, and vimentin genes are methylated in most colorectal neoplasms butrarely in normal epithelia.

Cancer screening is in need of a marker or marker panel for colorectalcancer that is broadly informative and exhibits high specificity forcolorectal cancer at the tissue level when interrogated in samples takenfrom a subject (e.g., a stool sample; a colorectal tissue sample).

Accordingly, provided herein is technology for colorectal cancerscreening markers that provide a high signal-to-noise ratio and a lowbackground level when detected from samples taken from a subject (e.g.,a stool sample; a colorectal tissue sample; serum sample; blood or bloodproduct).

In experiments conducted during the course of developing embodiments forthe present invention, markers were identified in a case-control studiesby comparing the methylation state of DNA markers from colorectal tissueof subjects with colorectal neoplasia, adenoma, and/or sessile serratedpolyps (SSP) to the methylation state of the same DNA markers fromcontrol subjects (e.g., normal tissue such as normal colon) (see,Examples 1-2, Tables 1-5).

For example, markers and/or panels of markers (e.g., a chromosomalregion having an annotation selected from FLI1, OPLAH, DTX1, MATK,SFMBT2 region 2, KCNK12, VAV3 region 1, SFMBT2 region 3, PPP2R5C, CHST2region 2, PKIA, PDGFD, ELOVL2, CHST2 region 1, SFMBT2 region 1, QKI,VAV3 region 2, and SLC8A3) were identified in a case-control study bycomparing the methylation state of DNA markers (e.g., from colorectaltissue of subjects with colorectal neoplasia and/or adenoma) to themethylation state of the same DNA markers from control subjects (e.g.,normal tissue such as normal colon) (see, Example 1 and Table 1).

Markers and/or panels of markers (e.g., a chromosomal region having anannotation selected from BMP3, NDRG4, PDGFG, CHST2, and SFMBT2) wereidentified in case-control studies by comparing the methylation state ofDNA markers from colorectal tissue of subjects having inflammatory boweldisease and colorectal cancer to the methylation state of the same DNAmarkers from control subjects (e.g., normal tissue such as normal colon)(see, Example 1 and Table 2).

In addition, 185, 244, and 111 DNA methylation markers specific forcolorectal cancers, large adenomas, and sessile serrated polyps,respectively, were identified (see, Example 2 and Tables 3, 4 and 5).Along with the colorectal cancer cases, large adenoma cases, and sessileserrated polyps cases, normal colonic mucosa, and normal white bloodcell DNA was sequenced.

Additional experiments conducted during the course of developingembodiments for the present invention demonstrated NDRG4, BMP3, OPLAH,FLI1, PDGFD, CHST_7889, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890,VAV3, and DTX1 as effective markers for detecting colorectal cancerwithin stool samples (see, Example 3 and Tables 6 and 7).

As described herein, the technology provides a number of methylated DNAmarkers and subsets thereof (e.g., sets of 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12 or more markers) with high discrimination for colorectalneoplasia (e.g., colorectal cancer, adenoma, SSP). Experiments applied aselection filter to candidate markers to identify markers that provide ahigh signal to noise ratio and a low background level to provide highspecificity, e.g., when assaying distant media (e.g., stool, blood,urine, metastatic tissue, etc.) for purposes of colorectal cancerscreening or diagnosis. As such, the technology provides for specificmarkers and marker combinations for purposes of colorectal cancerscreening or diagnosis.

In some embodiments, the technology is related to assessing the presenceof and methylation state of one or more of the markers identified hereinin a biological sample. These markers comprise one or moredifferentially methylated regions (DMR) as discussed herein, e.g., asprovided in Tables 1-6. Methylation state is assessed in embodiments ofthe technology. As such, the technology provided herein is notrestricted in the method by which a gene's methylation state ismeasured. For example, in some embodiments the methylation state ismeasured by a genome scanning method. For example, one method involvesrestriction landmark genomic scanning (Kawai et al. (1994) Mol. Cell.Biol. 14: 7421-7427) and another example involves methylation-sensitivearbitrarily primed PCR (Gonzalgo et al. (1997) Cancer Res. 57: 594-599).In some embodiments, changes in methylation patterns at specific CpGsites are monitored by digestion of genomic DNA withmethylation-sensitive restriction enzymes followed by Southern analysisof the regions of interest (digestion-Southern method). In someembodiments, analyzing changes in methylation patterns involves aPCR-based process that involves digestion of genomic DNA withmethylation-sensitive restriction enzymes prior to PCR amplification(Singer-Sam et al. (1990) Nucl. Acids Res. 18: 687). In addition, othertechniques have been reported that utilize bisulfite treatment of DNA asa starting point for methylation analysis. These includemethylation-specific PCR (MSP) (Herman et al. (1992) Proc. Natl. Acad.Sci. USA 93: 9821-9826) and restriction enzyme digestion of PCR productsamplified from bisulfite-converted DNA (Sadri and Hornsby (1996) Nucl.Acids Res. 24: 5058-5059; and Xiong and Laird (1997) Nucl. Acids Res.25: 2532-2534). PCR techniques have been developed for detection of genemutations (Kuppuswamy et al. (1991) Proc. Natl. Acad. Sci. USA 88:1143-1147) and quantification of allelic-specific expression (Szabo andMann (1995) Genes Dev. 9: 3097-3108; and Singer-Sam et al. (1992) PCRMethods Appl. 1: 160-163). Such techniques use internal primers, whichanneal to a PCR-generated template and terminate immediately 5′ of thesingle nucleotide to be assayed. Methods using a “quantitative Ms-SNuPEassay” as described in U.S. Pat. No. 7,037,650 are used in someembodiments.

Upon evaluating a methylation state, the methylation state is oftenexpressed as the fraction or percentage of individual strands of DNAthat is methylated at a particular site (e.g., at a single nucleotide,at a particular region or locus, at a longer sequence of interest, e.g.,up to a ˜100-bp, 200-bp, 500-bp, 1000-bp subsequence of a DNA or longer)relative to the total population of DNA in the sample comprising thatparticular site. Traditionally, the amount of the unmethylated nucleicacid is determined by PCR using calibrators. Then, a known amount of DNAis bisulfite treated and the resulting methylation-specific sequence isdetermined using either a real-time PCR or other exponentialamplification, e.g., a QuARTS assay (e.g., as provided by U.S. Pat. No.8,361,720; and U.S. Pat. Appl. Pub. Nos. 2012/0122088 and 2012/0122106).

For example, in some embodiments methods comprise generating a standardcurve for the unmethylated target by using external standards. Thestandard curve is constructed from at least two points and relates thereal-time Ct value for unmethylated DNA to known quantitative standards.Then, a second standard curve for the methylated target is constructedfrom at least two points and external standards. This second standardcurve relates the Ct for methylated DNA to known quantitative standards.Next, the test sample Ct values are determined for the methylated andunmethylated populations and the genomic equivalents of DNA arecalculated from the standard curves produced by the first two steps. Thepercentage of methylation at the site of interest is calculated from theamount of methylated DNAs relative to the total amount of DNAs in thepopulation, e.g., (number of methylated DNAs)/(the number of methylatedDNAs+number of unmethylated DNAs)×100.

According to another aspect of the present invention, neoplasia of abiological sample is indicated when a methylation ratio of one or moreDNA methylation markers relative to a level of bisulfite-treated DNAcopy number of a reference gene is different, wherein the one or moreDNA methylation markers comprises a base in a differentially methylatedregion (DMR) as provided herein. The methylation ratio includes theratio of the methylation level of the DNA methylation marker and thelevel of a region in a reference gene determined by the same means usedfor the determination of the methylation level of the biomarker.Usually, the methylation ratio is represented by the ratio of themethylation level of the DNA methylation marker and the level of aregion in a reference gene determined by the same means used for thedetermination of the methylation level of the DNA methylation marker.

In some embodiments, the methylation ratio is the ratio of themethylation level of a DNA methylation marker and the level of a regionof a reference gene, both of which are quantitatively measured usingreal-time polymerase chain reaction (PCR). For example, the methylationlevel of a DNA methylation marker from a sample of a subject can bequantitatively measured using a pair of primers and an oligonucleotideprobe, where one primer, both primers, the oligonucleotide probe, orboth primers and the oligonucleotide probe are capable of distinguishingbetween methylated and unmethylated nucleic acid, e.g., after thenucleic acid being modified by a modifying agent, e.g., bisulfiteconverting unmethylated cytosine to a converted nucleic acid.

The region of a reference gene of the present invention can be anyregion of a gene having one or more sites or regions that are devoid ofmethylation sites, e.g., devoid of CpG dinucleotides. For example, theregion of a reference gene can be a region that having two primerbinding sites for amplification such as PCR that are devoid of CpGdinucleotdies or a region having at least one specific oligonucleotideprobe binding site for real-time PCR that is devoid of CpGdinucleotides. In one aspect, the region of a reference gene of thepresent invention is a region of MYOD gene. In another aspect, theregion of a reference gene of the present invention is a region of ACTBgene. In yet another embodiment, the region of a reference gene of thepresent invention is a region that is not frequently subject to copynumber alterations, such as gene amplification or deletion.

In general, according to the present invention the level of a region ofa reference gene is quantitatively measured using real-time PCR withprimers and specific probes that specifically bind to sites afterbisulfite conversion but without discriminating directly or indirectlythe methylation status of the sites.

In certain embodiments, methods for detecting neoplasm in a subject areprovided. Such methods comprise, for example, obtaining a samplecomprising DNA from a subject; treating the obtained DNA with a reagentwhich selectively modifies unmethylated cytosine residues in theobtained DNA to produce modified residues but which does not modifymethylated cytosine residues; determining the methylation level of oneor more DNA methylation markers in the DNA having undergone the treatingof step b), wherein one or more DNA methylation markers comprises a basein a differentially methylated region (DMR) as provided herein;comparing the determined methylation level of the one or more DNAmethylation markers with methylation level references for the one ormore DNA methylation markers for subjects not having neoplasm; andidentifying the subject as having neoplasm when the methylation state ofor more of the DNA methylation markers is different than a methylationstate of the marker assayed in a subject that does not have a neoplasm.

In some embodiments, a determination of elevated methylation in one ormore of the DNA methylation markers comprises a determination of alteredmethylation within a region selected from the group consisting of a CpGisland and a CpG island shore.

In some embodiments, a determination of elevated methylation within saidCpG island or CpG shore comprises elevated methylation within a codingregion or a regulatory region of the DNA methylation marker.

In some embodiments, the determining the methylation level of one ormore DNA methylation markers in the DNA having undergone the treating ofstep b) comprises determining the methylation score and/or themethylation frequency of the one or more DNA methylation markers.

In some embodiments, the treating of step b) is accomplished throughbisulfite modification of the obtained DNA.

In some embodiments, the determining the methylation level of one ormore DNA methylation markers in the DNA having undergone the treating ofstep b) is achieved by a technique selected from the group consisting ofmethylation-specific PCR, quantitative methylation-specific PCR,methylation-sensitive DNA restriction enzyme analysis, quantitativebisulfite pyrosequencing, and bisulfite genomic sequencing PCR.

In some embodiments, the neoplasm is colorectal cancer, a largecolorectal adenoma, and/or a sessile serrated polyp.

In certain embodiments, methods for detecting neoplasm in a subject areprovided. Such embodiments comprise, for example, determining amethylation ratio of a sample from a subject, wherein the methylationratio is the level of methylation of a bisulfite-treated region of oneor more DNA methylation markers relative to a level of bisulfite-treatedDNA copy number of a reference gene, wherein the one or more DNAmethylation markers comprises a base in a differentially methylatedregion (DMR) as provided herein, wherein the reference gene is MYOD orACTB, identifying the subject as having neoplasm when the methylationratio of one or more of the DNA methylation markers is different thanthe methylation ratio of the respective marker assayed in a subject thatdoes not have a neoplasm.

In some embodiments, level of methylation is determined by usingreal-time polymerase chain reaction (PCR). In some embodiments, thelevel of methylation is determined by using real-time polymerase chainreaction (PCR), wherein at least one primer used in the PCR is capableof distinguishing between unmethylated and methylated nucleic acid. Insome embodiments, the level of methylation is determined by usingreal-time polymerase chain reaction (PCR), wherein both primers used inthe PCR are capable of distinguishing between unmethylated andmethylated nucleic acid. In some embodiments, the level of methylationis determined by using real-time polymerase chain reaction (PCR),wherein a probe used in the PCR is capable of distinguishing betweenunmethylated and methylated nucleic acid. In some embodiments, the levelof methylation is determined by using real-time polymerase chainreaction (PCR), wherein both primers and a probe used in the PCR arecapable of distinguishing between unmethylated and methylated nucleicacid. In some embodiments, the level of the region in the reference geneis determined by using real-time polymerase chain reaction (PCR). Insome embodiments, the level of the region in the reference gene isdetermined by using real-time polymerase chain reaction (PCR), whereinthe region contains a first and second primer binding site and a probebinding site and wherein the first and second primer binding site andthe probe binding site are devoid of CpG dinucleotides. In someembodiments, the region in the reference gene is devoid of CpGdinucleotides.

Also provided herein are compositions and kits for practicing themethods. For example, in some embodiments, reagents (e.g., primers,probes) specific for one or more markers are provided alone or in sets(e.g., sets of primers pairs for amplifying a plurality of markers).Additional reagents for conducting a detection assay may also beprovided (e.g., enzymes, buffers, positive and negative controls forconducting QuARTS, PCR, sequencing, bisulfite, or other assays). In someembodiments, the kits containing one or more reagent necessary,sufficient, or useful for conducting a method are provided. Alsoprovided are reactions mixtures containing the reagents. Furtherprovided are master mix reagent sets containing a plurality of reagentsthat may be added to each other and/or to a test sample to complete areaction mixture.

In some embodiments, the technology described herein is associated witha programmable machine designed to perform a sequence of arithmetic orlogical operations as provided by the methods described herein. Forexample, some embodiments of the technology are associated with (e.g.,implemented in) computer software and/or computer hardware. In oneaspect, the technology relates to a computer comprising a form ofmemory, an element for performing arithmetic and logical operations, anda processing element (e.g., a microprocessor) for executing a series ofinstructions (e.g., a method as provided herein) to read, manipulate,and store data. In some embodiments, a microprocessor is part of asystem for determining a methylation state (e.g., of one or more DMR,e.g. as provided in Tables 1-6); comparing methylation states (e.g., ofone or more DMR, e.g. as provided in Tables 1-6); generating standardcurves; determining a Ct value; calculating a fraction, frequency, orpercentage of methylation (e.g., of one or more DMR, e.g. as provided inTables 1-6); identifying a CpG island; determining a specificity and/orsensitivity of an assay or marker; calculating an ROC curve and anassociated AUC; sequence analysis; all as described herein or is knownin the art.

In some embodiments, a software or hardware component receives theresults of multiple assays and determines a single value result toreport to a user that indicates a cancer risk based on the results ofthe multiple assays (e.g., determining the methylation state of multipleDMR, e.g. as provided in Tables 1-6). Related embodiments calculate arisk factor based on a mathematical combination (e.g., a weightedcombination, a linear combination) of the results from multiple assays,e.g., determining the methylation states of multiple markers (such asmultiple DMR, e.g. as provided in Tables 1-6). In some embodiments, themethylation state of a DMR defines a dimension and may have values in amultidimensional space and the coordinate defined by the methylationstates of multiple DMR is a result, e.g., to report to a user, e.g.,related to a colorectal cancer risk.

Some embodiments comprise a storage medium and memory components. Memorycomponents (e.g., volatile and/or nonvolatile memory) find use instoring instructions (e.g., an embodiment of a process as providedherein) and/or data (e.g., a work piece such as methylationmeasurements, sequences, and statistical descriptions associatedtherewith). Some embodiments relate to systems also comprising one ormore of a CPU, a graphics card, and a user interface (e.g., comprisingan output device such as display and an input device such as akeyboard).

Programmable machines associated with the technology compriseconventional extant technologies and technologies in development or yetto be developed (e.g., a quantum computer, a chemical computer, a DNAcomputer, an optical computer, a spintronics based computer, etc.).

In some embodiments, the technology comprises a wired (e.g., metalliccable, fiber optic) or wireless transmission medium for transmittingdata. For example, some embodiments relate to data transmission over anetwork (e.g., a local area network (LAN), a wide area network (WAN), anad-hoc network, the internet, etc.). In some embodiments, programmablemachines are present on such a network as peers and in some embodimentsthe programmable machines have a client/server relationship.

In some embodiments, data are stored on a computer-readable storagemedium such as a hard disk, flash memory, optical media, a floppy disk,etc.

In some embodiments, the technology provided herein is associated with aplurality of programmable devices that operate in concert to perform amethod as described herein. For example, in some embodiments, aplurality of computers (e.g., connected by a network) may work inparallel to collect and process data, e.g., in an implementation ofcluster computing or grid computing or some other distributed computerarchitecture that relies on complete computers (with onboard CPUs,storage, power supplies, network interfaces, etc.) connected to anetwork (private, public, or the internet) by a conventional networkinterface, such as Ethernet, fiber optic, or by a wireless networktechnology.

For example, some embodiments provide a computer that includes acomputer-readable medium. The embodiment includes a random access memory(RAM) coupled to a processor. The processor executes computer-executableprogram instructions stored in memory. Such processors may include amicroprocessor, an ASIC, a state machine, or other processor, and can beany of a number of computer processors, such as processors from IntelCorporation of Santa Clara, Calif. and Motorola Corporation ofSchaumburg, Ill. Such processors include, or may be in communicationwith, media, for example computer-readable media, which storesinstructions that, when executed by the processor, cause the processorto perform the steps described herein.

Embodiments of computer-readable media include, but are not limited to,an electronic, optical, magnetic, or other storage or transmissiondevice capable of providing a processor with computer-readableinstructions. Other examples of suitable media include, but are notlimited to, a floppy disk, CD-ROM, DVD, magnetic disk, memory chip, ROM,RAM, an ASIC, a configured processor, all optical media, all magnetictape or other magnetic media, or any other medium from which a computerprocessor can read instructions. Also, various other forms ofcomputer-readable media may transmit or carry instructions to acomputer, including a router, private or public network, or othertransmission device or channel, both wired and wireless. Theinstructions may comprise code from any suitable computer-programminglanguage, including, for example, C, C++, C#, Visual Basic, Java,Python, Perl, and JavaScript.

Computers are connected in some embodiments to a network. Computers mayalso include a number of external or internal devices such as a mouse, aCD-ROM, DVD, a keyboard, a display, or other input or output devices.Examples of computers are personal computers, digital assistants,personal digital assistants, cellular phones, mobile phones, smartphones, pagers, digital tablets, laptop computers, internet appliances,and other processor-based devices. In general, the computers related toaspects of the technology provided herein may be any type ofprocessor-based platform that operates on any operating system, such asMicrosoft Windows, Linux, UNIX, Mac OS X, etc., capable of supportingone or more programs comprising the technology provided herein. Someembodiments comprise a personal computer executing other applicationprograms (e.g., applications). The applications can be contained inmemory and can include, for example, a word processing application, aspreadsheet application, an email application, an instant messengerapplication, a presentation application, an Internet browserapplication, a calendar/organizer application, and any other applicationcapable of being executed by a client device.

All such components, computers, and systems described herein asassociated with the technology may be logical or virtual.

Accordingly, provided herein is technology related to a method ofscreening for a colorectal neoplasm in a sample (e.g., stool sample,colorectal tissue sample; blood sample; blood product sample) obtainedfrom a subject (e.g., a human subject), the method comprising assaying amethylation state of a marker in a sample obtained from a subject; andidentifying the subject as having a colorectal neoplasm when themethylation state of the marker is different than a methylation state ofthe marker assayed in a subject that does not have a colorectalneoplasm, wherein the marker comprises a base in a differentiallymethylated region (DMR) selected from a group consisting of a DMR asprovided in Tables 1-6. The technology also encompasses determining thestate or stage of a colorectal cancer, e.g., in some embodiments theneoplasm is pre-cancerous. Some embodiments provide methods comprisingassaying a plurality of markers, e.g., comprising assaying 2 to 11markers.

The technology is not limited in the methylation state assessed. In someembodiments assessing the methylation state of the marker in the samplecomprises determining the methylation state of one base. In someembodiments, assaying the methylation state of the marker in the samplecomprises determining the extent of methylation at a plurality of bases.Moreover, in some embodiments the methylation state of the markercomprises an increased methylation of the marker relative to a normalmethylation state of the marker. In some embodiments, the methylationstate of the marker comprises a decreased methylation of the markerrelative to a normal methylation state of the marker. In someembodiments the methylation state of the marker comprises a differentpattern of methylation of the marker relative to a normal methylationstate of the marker.

Furthermore, in some embodiments the marker is a region of 100 or fewerbases, the marker is a region of 500 or fewer bases, the marker is aregion of 1000 or fewer bases, the marker is a region of 5000 or fewerbases, or, in some embodiments, the marker is one base. In someembodiments the marker is in a high CpG density promoter.

The technology is not limited by sample type. For example, in someembodiments the sample is a stool sample, a tissue sample, a colorectaltissue sample, a blood sample (e.g., plasma, serum, whole blood), anexcretion, or a urine sample.

Furthermore, the technology is not limited in the method used todetermine methylation state. In some embodiments the assaying comprisesusing methylation specific polymerase chain reaction, nucleic acidsequencing, mass spectrometry, methylation specific nuclease, mass-basedseparation, or target capture. In some embodiments, the assayingcomprises use of a methylation specific oligonucleotide. In someembodiments, the technology uses massively parallel sequencing (e.g.,next-generation sequencing) to determine methylation state, e.g.,sequencing-by-synthesis, real-time (e.g., single-molecule) sequencing,bead emulsion sequencing, nanopore sequencing, etc.

The technology provides reagents for detecting a DMR, e.g., in someembodiments are provided a set of oligonucleotides comprising thesequences provided by SEQ ID NOs: 1-110. In some embodiments areprovided an oligonucleotide comprising a sequence complementary to achromosomal region having a base in a DMR, e.g., an oligonucleotidesensitive to methylation state of a DMR.

The technology provides various panels of markers, e.g., in someembodiments the marker comprises a chromosomal region having anannotation that is FLI1, OPLAH, DTX1, MATK, SFMBT2 region 2, KCNK12,VAV3 region 1, SFMBT2 region 3, PPP2R5C, CHST2 region 2, PKIA, PDGFD,ELOVL2, CHST2 region 1, SFMBT2 region 1, QKI, VAV3 region 2, and SLC8A3,and that comprises the marker (see, Table 1). In some embodiments themarker comprises a chromosomal region having an annotation that is BMP3,NDRG4, PDGFG, CHST2, and SFMBT2, and that comprises the marker (see,Table 2). In some embodiments the marker comprises one or more of thechromosomal regions provided in Table 3 (for colorectal cancer), Table 4(for adenoma), and Table 5 (for SSP).

In addition, embodiments provide a method of analyzing a DMR from Tables1-6. Some embodiments provide determining the methylation state of amarker, wherein a chromosomal region having an annotation that is FLI1,OPLAH, DTX1, MATK, SFMBT2 region 2, KCNK12, VAV3 region 1, SFMBT2 region3, PPP2R5C, CHST2 region 2, PKIA, PDGFD, ELOVL2, CHST2 region 1, SFMBT2region 1, QKI, VAV3 region 2, and SLC8A3, and/or a chromosomal regionhaving an annotation that is BMP3, NDRG4, PDGFG, CHST2, and SFMBT2comprises the marker. Some embodiments provide determining themethylation state of a marker, wherein a chromosomal region as providedin Tables 3, 4 and/or 5 comprises the marker.

Kit embodiments are provided, e.g., a kit comprising a bisulfitereagent; and a control nucleic acid comprising a sequence from a DMRselected from any of the chromosomal regions provided in Tables 1-6 andhaving a methylation state associated with a subject who does not have acancer. In some embodiments, kits comprise a bisulfite reagent and anoligonucleotide as described herein. In some embodiments, kits comprisea bisulfite reagent; and a control nucleic acid comprising a sequencefrom a DMR selected from any of the chromosomal regions provided inTables 1-6 and having a methylation state associated with a subject whohas colorectal cancer, adenoma and/or SSP. Some kit embodiments comprisea sample collector for obtaining a sample from a subject (e.g., a stoolsample); reagents for isolating a nucleic acid from the sample; abisulfite reagent; and an oligonucleotide as described herein.

The technology is related to embodiments of compositions (e.g., reactionmixtures). In some embodiments are provided a composition comprising anucleic acid comprising a DMR and a bisulfite reagent. Some embodimentsprovide a composition comprising a nucleic acid comprising a DMR and anoligonucleotide as described herein. Some embodiments provide acomposition comprising a nucleic acid comprising a DMR and amethylation-sensitive restriction enzyme. Some embodiments provide acomposition comprising a nucleic acid comprising a DMR and a polymerase.

Additional related method embodiments are provided for screening for acolorectal neoplasm in a sample obtained from a subject, e.g., a methodcomprising determining a methylation state of a marker in the samplecomprising a base in a DMR selected from any of the chromosomal regionsprovided in Tables 1-6; comparing the methylation state of the markerfrom the subject sample to a methylation state of the marker from anormal control sample from a subject who does not have a cancer; anddetermining a confidence interval and/or a p value of the difference inthe methylation state of the subject sample and the normal controlsample. In some embodiments, the confidence interval is 90%, 95%, 97.5%,98%, 99%, 99.5%, 99.9% or 99.99% and the p value is 0.1, 0.05, 0.025,0.02, 0.01, 0.005, 0.001, or 0.0001. Some embodiments of methods providesteps of reacting a nucleic acid comprising a DMR with a bisulfitereagent to produce a bisulfite-reacted nucleic acid; sequencing thebisulfite-reacted nucleic acid to provide a nucleotide sequence of thebisulfite-reacted nucleic acid; comparing the nucleotide sequence of thebisulfite-reacted nucleic acid with a nucleotide sequence of a nucleicacid comprising the DMR from a subject who does not have a cancer toidentify differences in the two sequences; and identifying the subjectas having a colorectal neoplasm when a difference is present.

Systems for screening for a colorectal neoplasm in a sample obtainedfrom a subject are provided by the technology. Exemplary embodiments ofsystems include, e.g., a system for screening for a colorectal neoplasmin a sample obtained from a subject, the system comprising an analysiscomponent configured to determine the methylation state of a sample, asoftware component configured to compare the methylation state of thesample with a control sample or a reference sample methylation staterecorded in a database, and an alert component configured to alert auser of a cancer-associated methylation state. An alert is determined insome embodiments by a software component that receives the results frommultiple assays (e.g., determining the methylation states of multiplemarkers, e.g., DMR, e.g., as provided in Tables 1-6) and calculating avalue or result to report based on the multiple results. Someembodiments provide a database of weighted parameters associated witheach DMR provided herein for use in calculating a value or result and/oran alert to report to a user (e.g., such as a physician, nurse,clinician, etc.). In some embodiments all results from multiple assaysare reported and in some embodiments one or more results are used toprovide a score, value, or result based on a composite of one or moreresults from multiple assays that is indicative of a colorectal cancerrisk in a subject.

In some embodiments of systems, a sample comprises a nucleic acidcomprising a DMR. In some embodiments the system further comprises acomponent for isolating a nucleic acid, a component for collecting asample such as a component for collecting a stool sample. In someembodiments, the system comprises nucleic acid sequences comprising aDMR. In some embodiments the database comprises nucleic acid sequencesfrom subjects who do not have a cancer. Also provided are nucleic acids,e.g., a set of nucleic acids, each nucleic acid having a sequencecomprising a DMR. In some embodiments the set of nucleic acids whereineach nucleic acid has a sequence from a subject who does not have acancer. Related system embodiments comprise a set of nucleic acids asdescribed and a database of nucleic acid sequences associated with theset of nucleic acids. Some embodiments further comprise a bisulfitereagent. And, some embodiments further comprise a nucleic acidsequencer.

The technology is related to embodiments of compositions (e.g., reactionmixtures). In some embodiments are provided a composition comprising anucleic acid comprising a DMR (e.g., a DMR as provided in Tables 1-6)and a bisulfite reagent. Some embodiments provide a compositioncomprising a nucleic acid comprising a DMR and an oligonucleotide asdescribed herein. Some embodiments provide a composition comprising anucleic acid comprising a DMR and a methylation-sensitive restrictionenzyme. Some embodiments provide a composition comprising a nucleic acidcomprising a DMR and a polymerase.

In certain embodiments, the present invention provides methods ofscreening for a colorectal neoplasm in a sample obtained from a subjecthaving inflammatory bowel disease, the method comprising 1) assaying amethylation state of a marker in a sample obtained from a subject; and2) identifying the subject as having a neoplasm when the methylationstate of the marker is different than a methylation state of the markerassayed in a subject that does not have a neoplasm, wherein the markercomprises a base in a differentially methylated region (DMR) as providedin Table 2. In some embodiments, the neoplasm is colorectal cancerand/or flat dysplasia.

Additional embodiments will be apparent to persons skilled in therelevant art based on the teachings contained herein.

DETAILED DESCRIPTION

Provided herein is technology relating to detecting colorectal neoplasiaand particularly, but not exclusively, to methods, compositions, andrelated uses for detecting premalignant and malignant colorectal cancer.As the technology is described herein, the section headings used are fororganizational purposes only and are not to be construed as limiting thesubject matter in any way.

In this detailed description of the various embodiments, for purposes ofexplanation, numerous specific details are set forth to provide athorough understanding of the embodiments disclosed. One skilled in theart will appreciate, however, that these various embodiments may bepracticed with or without these specific details. In other instances,structures and devices are shown in block diagram form. Furthermore, oneskilled in the art can readily appreciate that the specific sequences inwhich methods are presented and performed are illustrative and it iscontemplated that the sequences can be varied and still remain withinthe spirit and scope of the various embodiments disclosed herein.

All literature and similar materials cited in this application,including but not limited to, patents, patent applications, articles,books, treatises, and internet web pages are expressly incorporated byreference in their entirety for any purpose. Unless defined otherwise,all technical and scientific terms used herein have the same meaning asis commonly understood by one of ordinary skill in the art to which thevarious embodiments described herein belongs. When definitions of termsin incorporated references appear to differ from the definitionsprovided in the present teachings, the definition provided in thepresent teachings shall control.

DEFINITIONS

To facilitate an understanding of the present technology, a number ofterms and phrases are defined below. Additional definitions are setforth throughout the detailed description.

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments of the invention may be readilycombined, without departing from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or” operatorand is equivalent to the term “and/or” unless the context clearlydictates otherwise. The term “based on” is not exclusive and allows forbeing based on additional factors not described, unless the contextclearly dictates otherwise. In addition, throughout the specification,the meaning of “a”, “an”, and “the” include plural references. Themeaning of “in” includes “in” and “on.”

As used herein, a “nucleic acid” or “nucleic acid molecule” generallyrefers to any ribonucleic acid or deoxyribonucleic acid, which may beunmodified or modified DNA or RNA. “Nucleic acids” include, withoutlimitation, single- and double-stranded nucleic acids. As used herein,the term “nucleic acid” also includes DNA as described above thatcontains one or more modified bases. Thus, DNA with a backbone modifiedfor stability or for other reasons is a “nucleic acid”. The term“nucleic acid” as it is used herein embraces such chemically,enzymatically, or metabolically modified forms of nucleic acids, as wellas the chemical forms of DNA characteristic of viruses and cells,including for example, simple and complex cells.

The terms “oligonucleotide” or “polynucleotide” or “nucleotide” or“nucleic acid” refer to a molecule having two or moredeoxyribonucleotides or ribonucleotides, preferably more than three, andusually more than ten. The exact size will depend on many factors, whichin turn depends on the ultimate function or use of the oligonucleotide.The oligonucleotide may be generated in any manner, including chemicalsynthesis, DNA replication, reverse transcription, or a combinationthereof. Typical deoxyribonucleotides for DNA are thymine, adenine,cytosine, and guanine Typical ribonucleotides for RNA are uracil,adenine, cytosine, and guanine.

As used herein, the terms “locus” or “region” of a nucleic acid refer toa subregion of a nucleic acid, e.g., a gene on a chromosome, a singlenucleotide, a CpG island, etc.

The terms “complementary” and “complementarity” refer to nucleotides(e.g., 1 nucleotide) or polynucleotides (e.g., a sequence ofnucleotides) related by the base-pairing rules. For example, thesequence 5′-A-G-T-3′ is complementary to the sequence 3′-T-C-A-5′.Complementarity may be “partial,” in which only some of the nucleicacids' bases are matched according to the base pairing rules. Or, theremay be “complete” or “total” complementarity between the nucleic acids.The degree of complementarity between nucleic acid strands effects theefficiency and strength of hybridization between nucleic acid strands.This is of particular importance in amplification reactions and indetection methods that depend upon binding between nucleic acids.

The term “gene” refers to a nucleic acid (e.g., DNA or RNA) sequencethat comprises coding sequences necessary for the production of an RNA,or of a polypeptide or its precursor. A functional polypeptide can beencoded by a full length coding sequence or by any portion of the codingsequence as long as the desired activity or functional properties (e.g.,enzymatic activity, ligand binding, signal transduction, etc.) of thepolypeptide are retained. The term “portion” when used in reference to agene refers to fragments of that gene. The fragments may range in sizefrom a few nucleotides to the entire gene sequence minus one nucleotide.Thus, “a nucleotide comprising at least a portion of a gene” maycomprise fragments of the gene or the entire gene.

The term “gene” also encompasses the coding regions of a structural geneand includes sequences located adjacent to the coding region on both the5′ and 3′ ends, e.g., for a distance of about 1 kb on either end, suchthat the gene corresponds to the length of the full-length mRNA (e.g.,comprising coding, regulatory, structural and other sequences). Thesequences that are located 5′ of the coding region and that are presenton the mRNA are referred to as 5′ non-translated or untranslatedsequences. The sequences that are located 3′ or downstream of the codingregion and that are present on the mRNA are referred to as 3′non-translated or 3′ untranslated sequences. The term “gene” encompassesboth cDNA and genomic forms of a gene. In some organisms (e.g.,eukaryotes), a genomic form or clone of a gene contains the codingregion interrupted with non-coding sequences termed “introns” or“intervening regions” or “intervening sequences.” Introns are segmentsof a gene that are transcribed into nuclear RNA (hnRNA); introns maycontain regulatory elements such as enhancers. Introns are removed or“spliced out” from the nuclear or primary transcript; introns thereforeare absent in the messenger RNA (mRNA) transcript. The mRNA functionsduring translation to specify the sequence or order of amino acids in anascent polypeptide.

In addition to containing introns, genomic forms of a gene may alsoinclude sequences located on both the 5′ and 3′ ends of the sequencesthat are present on the RNA transcript. These sequences are referred toas “flanking” sequences or regions (these flanking sequences are located5′ or 3′ to the non-translated sequences present on the mRNAtranscript). The 5′ flanking region may contain regulatory sequencessuch as promoters and enhancers that control or influence thetranscription of the gene. The 3′ flanking region may contain sequencesthat direct the termination of transcription, posttranscriptionalcleavage, and polyadenylation.

The term “wild-type” when made in reference to a gene refers to a genethat has the characteristics of a gene isolated from a naturallyoccurring source. The term “wild-type” when made in reference to a geneproduct refers to a gene product that has the characteristics of a geneproduct isolated from a naturally occurring source. The term“naturally-occurring” as applied to an object refers to the fact that anobject can be found in nature. For example, a polypeptide orpolynucleotide sequence that is present in an organism (includingviruses) that can be isolated from a source in nature and which has notbeen intentionally modified by the hand of a person in the laboratory isnaturally-occurring. A wild-type gene is often that gene or allele thatis most frequently observed in a population and is thus arbitrarilydesignated the “normal” or “wild-type” form of the gene. In contrast,the term “modified” or “mutant” when made in reference to a gene or to agene product refers, respectively, to a gene or to a gene product thatdisplays modifications in sequence and/or functional properties (e.g.,altered characteristics) when compared to the wild-type gene or geneproduct. It is noted that naturally-occurring mutants can be isolated;these are identified by the fact that they have altered characteristicswhen compared to the wild-type gene or gene product.

The term “allele” refers to a variation of a gene; the variationsinclude but are not limited to variants and mutants, polymorphic loci,and single nucleotide polymorphic loci, frameshift, and splicemutations. An allele may occur naturally in a population or it mightarise during the lifetime of any particular individual of thepopulation.

Thus, the terms “variant” and “mutant” when used in reference to anucleotide sequence refer to a nucleic acid sequence that differs by oneor more nucleotides from another, usually related, nucleotide acidsequence. A “variation” is a difference between two different nucleotidesequences; typically, one sequence is a reference sequence.

“Amplification” is a special case of nucleic acid replication involvingtemplate specificity. It is to be contrasted with non-specific templatereplication (e.g., replication that is template-dependent but notdependent on a specific template). Template specificity is heredistinguished from fidelity of replication (e.g., synthesis of theproper polynucleotide sequence) and nucleotide (ribo- or deoxyribo-)specificity. Template specificity is frequently described in terms of“target” specificity. Target sequences are “targets” in the sense thatthey are sought to be sorted out from other nucleic acid. Amplificationtechniques have been designed primarily for this sorting out.

Amplification of nucleic acids generally refers to the production ofmultiple copies of a polynucleotide, or a portion of the polynucleotide,typically starting from a small amount of the polynucleotide (e.g., asingle polynucleotide molecule, 10 to 100 copies of a polynucleotidemolecule, which may or may not be exactly the same), where theamplification products or amplicons are generally detectable.Amplification of polynucleotides encompasses a variety of chemical andenzymatic processes. The generation of multiple DNA copies from one or afew copies of a target or template DNA molecule during a polymerasechain reaction (PCR) or a ligase chain reaction (LCR; see, e.g., U.S.Pat. No. 5,494,810) are forms of amplification. Additional types ofamplification include, but are not limited to, allele-specific PCR (U.S.Pat. No. 5,639,611), assembly PCR (U.S. Pat. No. 5,965,408),helicase-dependent amplification (U.S. Pat. No. 7,662,594), Hot-startPCR (U.S. Pat. Nos. 5,773,258 and 5,338,671), intersequence-specfic PCR,inverse PCR (Triglia, et al. (1988) Nucleic Acids Res., 16:8186),ligation-mediated PCR (Guilfoyle, R. et al., Nucleic Acids Research,25:1854-1858 (1997); U.S. Pat. No. 5,508,169), methylation-specific PCR(Herman, et al., (1996) PNAS 93(13) 9821-9826), miniprimer PCR,multiplex ligation-dependent probe amplification (Schouten, et al.,(2002) Nucleic Acids Research 30(12): e57), multiplex PCR (Chamberlain,et al., (1988) Nucleic Acids Research 16(23) 11141-11156; Ballabio, etal., (1990) Human Genetics 84(6) 571-573; Hayden, et al., (2008) BMCGenetics 9:80), nested PCR, overlap-extension PCR (Higuchi, et al.,(1988) Nucleic Acids Research 16(15) 7351-7367), real time PCR (Higuchi,et al., (1992) Biotechnology 10:413-417; Higuchi, et al., (1993)Biotechnology 11:1026-1030), reverse transcription PCR (Bustin, S. A.(2000) J. Molecular Endocrinology 25:169-193), solid phase PCR, thermalasymmetric interlaced PCR, and Touchdown PCR (Don, et al., Nucleic AcidsResearch (1991) 19(14) 4008; Roux, K. (1994) Biotechniques 16(5)812-814; Hecker, et al., (1996) Biotechniques 20(3) 478-485).Polynucleotide amplification also can be accomplished using digital PCR(Kalinina, et al., Nucleic Acids Research. 25; 1999-2004, (1997);Vogelstein and Kinzler, Proc Natl Acad Sci USA. 96; 9236-41, (1999);International Patent Publication No. WO05023091A2; US Patent ApplicationPublication No. 20070202525).

As used herein, the term “nucleic acid detection assay” refers to anymethod of determining the nucleotide composition of a nucleic acid ofinterest. Nucleic acid detection assay include but are not limited to,DNA sequencing methods, probe hybridization methods, structure specificcleavage assays (e.g., the INVADER assay, Hologic, Inc.) and aredescribed, e.g., in U.S. Pat. Nos. 5,846,717, 5,985,557, 5,994,069,6,001,567, 6,090,543, and 6,872,816; Lyamichev et al., Nat. Biotech.,17:292 (1999), Hall et al., PNAS, USA, 97:8272 (2000), and US2009/0253142); polymerase chain reaction; branched hybridization methods(e.g., Chiron, U.S. Pat. Nos. 5,849,481, 5,710,264, 5,124,246, and5,624,802); rolling circle replication (e.g., U.S. Pat. Nos. 6,210,884,6,183,960 and 6,235,502); NASBA (e.g., U.S. Pat. No. 5,409,818);molecular beacon technology (e.g., U.S. Pat. No. 6,150,097); cyclingprobe technology (e.g., U.S. Pat. Nos. 5,403,711, 5,011,769, and5,660,988); ligase chain reaction (e.g., Barnay Proc. Natl. Acad. SciUSA 88, 189-93 (1991)); QuARTS assay (e.g., as provided by U.S. Pat. No.8,361,720; and U.S. Pat. Appl. Pub. Nos. 2012/0122088 and 2012/0122106);and sandwich hybridization methods (e.g., U.S. Pat. No. 5,288,609).

The term “primer” refers to an oligonucleotide, whether occurringnaturally as in a purified restriction digest or produced synthetically,that is capable of acting as a point of initiation of synthesis whenplaced under conditions in which synthesis of a primer extension productthat is complementary to a nucleic acid strand is induced, (e.g., in thepresence of nucleotides and an inducing agent such as a DNA polymeraseand at a suitable temperature and pH). The primer is preferably singlestranded for maximum efficiency in amplification, but may alternativelybe double stranded. If double stranded, the primer is first treated toseparate its strands before being used to prepare extension products.Preferably, the primer is an oligodeoxyribonucleotide. The primer mustbe sufficiently long to prime the synthesis of extension products in thepresence of the inducing agent. The exact lengths of the primers willdepend on many factors, including temperature, source of primer, and theuse of the method.

The term “probe” refers to an oligonucleotide (e.g., a sequence ofnucleotides), whether occurring naturally as in a purified restrictiondigest or produced synthetically, recombinantly, or by PCRamplification, that is capable of hybridizing to another oligonucleotideof interest. A probe may be single-stranded or double-stranded. Probesare useful in the detection, identification, and isolation of particulargene sequences (e.g., a “capture probe”). It is contemplated that anyprobe used in the present invention may, in some embodiments, be labeledwith any “reporter molecule,” so that is detectable in any detectionsystem, including, but not limited to enzyme (e.g., ELISA, as well asenzyme-based histochemical assays), fluorescent, radioactive, andluminescent systems. It is not intended that the present invention belimited to any particular detection system or label.

As used herein, “methylation” refers to cytosine methylation atpositions C5 or N4 of cytosine, the N6 position of adenine, or othertypes of nucleic acid methylation. In vitro amplified DNA is usuallyunmethylated because typical in vitro DNA amplification methods do notretain the methylation pattern of the amplification template. However,“unmethylated DNA” or “methylated DNA” can also refer to amplified DNAwhose original template was unmethylated or methylated, respectively.

Accordingly, as used herein a “methylated nucleotide” or a “methylatednucleotide base” refers to the presence of a methyl moiety on anucleotide base, where the methyl moiety is not present in a recognizedtypical nucleotide base. For example, cytosine does not contain a methylmoiety on its pyrimidine ring, but 5-methylcytosine contains a methylmoiety at position 5 of its pyrimidine ring. Therefore, cytosine is nota methylated nucleotide and 5-methylcytosine is a methylated nucleotide.In another example, thymine contains a methyl moiety at position 5 ofits pyrimidine ring; however, for purposes herein, thymine is notconsidered a methylated nucleotide when present in DNA since thymine isa typical nucleotide base of DNA.

As used herein, a “methylated nucleic acid molecule” refers to a nucleicacid molecule that contains one or more methylated nucleotides.

As used herein, a “methylation state”, “methylation profile”, and“methylation status” of a nucleic acid molecule refers to the presenceof absence of one or more methylated nucleotide bases in the nucleicacid molecule. For example, a nucleic acid molecule containing amethylated cytosine is considered methylated (e.g., the methylationstate of the nucleic acid molecule is methylated). A nucleic acidmolecule that does not contain any methylated nucleotides is consideredunmethylated.

The methylation state of a particular nucleic acid sequence (e.g., agene marker or DNA region as described herein) can indicate themethylation state of every base in the sequence or can indicate themethylation state of a subset of the bases (e.g., of one or morecytosines) within the sequence, or can indicate information regardingregional methylation density within the sequence with or withoutproviding precise information of the locations within the sequence themethylation occurs.

The methylation state of a nucleotide locus in a nucleic acid moleculerefers to the presence or absence of a methylated nucleotide at aparticular locus in the nucleic acid molecule. For example, themethylation state of a cytosine at the 7th nucleotide in a nucleic acidmolecule is methylated when the nucleotide present at the 7th nucleotidein the nucleic acid molecule is 5-methylcytosine. Similarly, themethylation state of a cytosine at the 7th nucleotide in a nucleic acidmolecule is unmethylated when the nucleotide present at the 7thnucleotide in the nucleic acid molecule is cytosine (and not5-methylcytosine).

The methylation status can optionally be represented or indicated by a“methylation value” (e.g., representing a methylation frequency,fraction, ratio, percent, etc.) A methylation value can be generated,for example, by quantifying the amount of intact nucleic acid presentfollowing restriction digestion with a methylation dependent restrictionenzyme or by comparing amplification profiles after bisulfite reactionor by comparing sequences of bisulfite-treated and untreated nucleicacids. Accordingly, a value, e.g., a methylation value, represents themethylation status and can thus be used as a quantitative indicator ofmethylation status across multiple copies of a locus. This is ofparticular use when it is desirable to compare the methylation status ofa sequence in a sample to a threshold or reference value.

As used herein, “methylation frequency” or “methylation percent (%)”refer to the number of instances in which a molecule or locus ismethylated relative to the number of instances the molecule or locus isunmethylated.

As such, the methylation state describes the state of methylation of anucleic acid (e.g., a genomic sequence). In addition, the methylationstate refers to the characteristics of a nucleic acid segment at aparticular genomic locus relevant to methylation. Such characteristicsinclude, but are not limited to, whether any of the cytosine (C)residues within this DNA sequence are methylated, the location ofmethylated C residue(s), the frequency or percentage of methylated Cthroughout any particular region of a nucleic acid, and allelicdifferences in methylation due to, e.g., difference in the origin of thealleles. The terms “methylation state”, “methylation profile”, and“methylation status” also refer to the relative concentration, absoluteconcentration, or pattern of methylated C or unmethylated C throughoutany particular region of a nucleic acid in a biological sample. Forexample, if the cytosine (C) residue(s) within a nucleic acid sequenceare methylated it may be referred to as “hypermethylated” or having“increased methylation”, whereas if the cytosine (C) residue(s) within aDNA sequence are not methylated it may be referred to as“hypomethylated” or having “decreased methylation”. Likewise, if thecytosine (C) residue(s) within a nucleic acid sequence are methylated ascompared to another nucleic acid sequence (e.g., from a different regionor from a different individual, etc.) that sequence is consideredhypermethylated or having increased methylation compared to the othernucleic acid sequence. Alternatively, if the cytosine (C) residue(s)within a DNA sequence are not methylated as compared to another nucleicacid sequence (e.g., from a different region or from a differentindividual, etc.) that sequence is considered hypomethylated or havingdecreased methylation compared to the other nucleic acid sequence.Additionally, the term “methylation pattern” as used herein refers tothe collective sites of methylated and unmethylated nucleotides over aregion of a nucleic acid. Two nucleic acids may have the same or similarmethylation frequency or methylation percent but have differentmethylation patterns when the number of methylated and unmethylatednucleotides are the same or similar throughout the region but thelocations of methylated and unmethylated nucleotides are different.Sequences are said to be “differentially methylated” or as having a“difference in methylation” or having a “different methylation state”when they differ in the extent (e.g., one has increased or decreasedmethylation relative to the other), frequency, or pattern ofmethylation. The term “differential methylation” refers to a differencein the level or pattern of nucleic acid methylation in a cancer positivesample as compared with the level or pattern of nucleic acid methylationin a cancer negative sample. It may also refer to the difference inlevels or patterns between patients that have recurrence of cancer aftersurgery versus patients who not have recurrence. Differentialmethylation and specific levels or patterns of DNA methylation areprognostic and predictive biomarkers, e.g., once the correct cut-off orpredictive characteristics have been defined.

Methylation state frequency can be used to describe a population ofindividuals or a sample from a single individual. For example, anucleotide locus having a methylation state frequency of 50% ismethylated in 50% of instances and unmethylated in 50% of instances.Such a frequency can be used, for example, to describe the degree towhich a nucleotide locus or nucleic acid region is methylated in apopulation of individuals or a collection of nucleic acids. Thus, whenmethylation in a first population or pool of nucleic acid molecules isdifferent from methylation in a second population or pool of nucleicacid molecules, the methylation state frequency of the first populationor pool will be different from the methylation state frequency of thesecond population or pool. Such a frequency also can be used, forexample, to describe the degree to which a nucleotide locus or nucleicacid region is methylated in a single individual. For example, such afrequency can be used to describe the degree to which a group of cellsfrom a tissue sample are methylated or unmethylated at a nucleotidelocus or nucleic acid region.

As used herein a “nucleotide locus” refers to the location of anucleotide in a nucleic acid molecule. A nucleotide locus of amethylated nucleotide refers to the location of a methylated nucleotidein a nucleic acid molecule.

Typically, methylation of human DNA occurs on a dinucleotide sequenceincluding an adjacent guanine and cytosine where the cytosine is located5′ of the guanine (also termed CpG dinucleotide sequences). Mostcytosines within the CpG dinucleotides are methylated in the humangenome, however some remain unmethylated in specific CpG dinucleotiderich genomic regions, known as CpG islands (see, e.g, Antequera et al.(1990) Cell 62: 503-514).

As used herein, a “CpG island” refers to a G:C-rich region of genomicDNA containing an increased number of CpG dinucleotides relative tototal genomic DNA. A CpG island can be at least 100, 200, or more basepairs in length, where the G:C content of the region is at least 50% andthe ratio of observed CpG frequency over expected frequency is 0.6; insome instances, a CpG island can be at least 500 base pairs in length,where the G:C content of the region is at least 55%) and the ratio ofobserved CpG frequency over expected frequency is 0.65. The observed CpGfrequency over expected frequency can be calculated according to themethod provided in Gardiner-Garden et al (1987) J. Mol. Biol. 196:261-281. For example, the observed CpG frequency over expected frequencycan be calculated according to the formula R=(A×B)/(C×D), where R is theratio of observed CpG frequency over expected frequency, A is the numberof CpG dinucleotides in an analyzed sequence, B is the total number ofnucleotides in the analyzed sequence, C is the total number of Cnucleotides in the analyzed sequence, and D is the total number of Gnucleotides in the analyzed sequence. Methylation state is typicallydetermined in CpG islands, e.g., at promoter regions. It will beappreciated though that other sequences in the human genome are prone toDNA methylation such as CpA and CpT (see Ramsahoye (2000) Proc. Natl.Acad. Sci. USA 97: 5237-5242; Salmon and Kaye (1970) Biochim. Biophys.Acta. 204: 340-351; Grafstrom (1985) Nucleic Acids Res. 13: 2827-2842;Nyce (1986) Nucleic Acids Res. 14: 4353-4367; Woodcock (1987) Biochem.Biophys. Res. Commun. 145: 888-894).

As used herein, a reagent that modifies a nucleotide of the nucleic acidmolecule as a function of the methylation state of the nucleic acidmolecule, or a methylation-specific reagent, refers to a compound orcomposition or other agent that can change the nucleotide sequence of anucleic acid molecule in a manner that reflects the methylation state ofthe nucleic acid molecule. Methods of treating a nucleic acid moleculewith such a reagent can include contacting the nucleic acid moleculewith the reagent, coupled with additional steps, if desired, toaccomplish the desired change of nucleotide sequence. Such a change inthe nucleic acid molecule's nucleotide sequence can result in a nucleicacid molecule in which each methylated nucleotide is modified to adifferent nucleotide. Such a change in the nucleic acid nucleotidesequence can result in a nucleic acid molecule in which eachunmethylated nucleotide is modified to a different nucleotide. Such achange in the nucleic acid nucleotide sequence can result in a nucleicacid molecule in which each of a selected nucleotide which isunmethylated (e.g., each unmethylated cytosine) is modified to adifferent nucleotide. Use of such a reagent to change the nucleic acidnucleotide sequence can result in a nucleic acid molecule in which eachnucleotide that is a methylated nucleotide (e.g., each methylatedcytosine) is modified to a different nucleotide. As used herein, use ofa reagent that modifies a selected nucleotide refers to a reagent thatmodifies one nucleotide of the four typically occurring nucleotides in anucleic acid molecule (C, G, T, and A for DNA and C, G, U, and A forRNA), such that the reagent modifies the one nucleotide withoutmodifying the other three nucleotides. In one exemplary embodiment, sucha reagent modifies an unmethylated selected nucleotide to produce adifferent nucleotide. In another exemplary embodiment, such a reagentcan deaminate unmethylated cytosine nucleotides. An exemplary reagent isbisulfite.

As used herein, the term “bisulfite reagent” refers to a reagentcomprising in some embodiments bisulfite, disulfite, hydrogen sulfite,or combinations thereof to distinguish between methylated andunmethylated cytidines, e.g., in CpG dinucleotide sequences.

The term “methylation assay” refers to any assay for determining themethylation state of one or more CpG dinucleotide sequences within asequence of a nucleic acid.

The term “MS AP-PCR” (Methylation-Sensitive Arbitrarily-PrimedPolymerase Chain Reaction) refers to the art-recognized technology thatallows for a global scan of the genome using CG-rich primers to focus onthe regions most likely to contain CpG dinucleotides, and described byGonzalgo et al. (1997) Cancer Research 57: 594-599.

The term “MethyLight™” refers to the art-recognized fluorescence-basedreal-time PCR technique described by Eads et al. (1999) Cancer Res. 59:2302-2306.

The term “HeavyMethyl™” refers to an assay wherein methylation specificblocking probes (also referred to herein as blockers) covering CpGpositions between, or covered by, the amplification primers enablemethylation-specific selective amplification of a nucleic acid sample.

The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™MethyLight™ assay, which is a variation of the MethyLight™ assay,wherein the MethyLight™ assay is combined with methylation specificblocking probes covering CpG positions between the amplificationprimers.

The term “Ms-SNuPE” (Methylation-sensitive Single Nucleotide PrimerExtension) refers to the art-recognized assay described by Gonzalgo &Jones (1997) Nucleic Acids Res. 25: 2529-2531.

The term “MSP” (Methylation-specific PCR) refers to the art-recognizedmethylation assay described by Herman et al. (1996) Proc. Natl. Acad.Sci. USA 93: 9821-9826, and by U.S. Pat. No. 5,786,146.

The term “COBRA” (Combined Bisulfite Restriction Analysis) refers to theart-recognized methylation assay described by Xiong & Laird (1997)Nucleic Acids Res. 25: 2532-2534.

The term “MCA” (Methylated CpG Island Amplification) refers to themethylation assay described by Toyota et al. (1999) Cancer Res. 59:2307-12, and in WO 00/26401A1.

As used herein, a “selected nucleotide” refers to one nucleotide of thefour typically occurring nucleotides in a nucleic acid molecule (C, G,T, and A for DNA and C, G, U, and A for RNA), and can include methylatedderivatives of the typically occurring nucleotides (e.g., when C is theselected nucleotide, both methylated and unmethylated C are includedwithin the meaning of a selected nucleotide), whereas a methylatedselected nucleotide refers specifically to a methylated typicallyoccurring nucleotide and an unmethylated selected nucleotides refersspecifically to an unmethylated typically occurring nucleotide.

The terms “methylation-specific restriction enzyme” or“methylation-sensitive restriction enzyme” refers to an enzyme thatselectively digests a nucleic acid dependent on the methylation state ofits recognition site. In the case of a restriction enzyme thatspecifically cuts if the recognition site is not methylated or ishemimethylated, the cut will not take place or will take place with asignificantly reduced efficiency if the recognition site is methylated.In the case of a restriction enzyme that specifically cuts if therecognition site is methylated, the cut will not take place or will takeplace with a significantly reduced efficiency if the recognition site isnot methylated. Preferred are methylation-specific restriction enzymes,the recognition sequence of which contains a CG dinucleotide (forinstance a recognition sequence such as CGCG or CCCGGG). Furtherpreferred for some embodiments are restriction enzymes that do not cutif the cytosine in this dinucleotide is methylated at the carbon atomC5.

As used herein, a “different nucleotide” refers to a nucleotide that ischemically different from a selected nucleotide, typically such that thedifferent nucleotide has Watson-Crick base-pairing properties thatdiffer from the selected nucleotide, whereby the typically occurringnucleotide that is complementary to the selected nucleotide is not thesame as the typically occurring nucleotide that is complementary to thedifferent nucleotide. For example, when C is the selected nucleotide, Uor T can be the different nucleotide, which is exemplified by thecomplementarity of C to G and the complementarity of U or T to A. Asused herein, a nucleotide that is complementary to the selectednucleotide or that is complementary to the different nucleotide refersto a nucleotide that base-pairs, under high stringency conditions, withthe selected nucleotide or different nucleotide with higher affinitythan the complementary nucleotide's base-paring with three of the fourtypically occurring nucleotides. An example of complementarity isWatson-Crick base pairing in DNA (e.g., A-T and C-G) and RNA (e.g., A-Uand C-G). Thus, for example, G base-pairs, under high stringencyconditions, with higher affinity to C than G base-pairs to G, A, or Tand, therefore, when C is the selected nucleotide, G is a nucleotidecomplementary to the selected nucleotide.

As used herein, the “sensitivity” of a given marker refers to thepercentage of samples that report a DNA methylation value above athreshold value that distinguishes between neoplastic and non-neoplasticsamples. In some embodiments, a positive is defined as ahistology-confirmed neoplasia that reports a DNA methylation value abovea threshold value (e.g., the range associated with disease), and a falsenegative is defined as a histology-confirmed neoplasia that reports aDNA methylation value below the threshold value (e.g., the rangeassociated with no disease). The value of sensitivity, therefore,reflects the probability that a DNA methylation measurement for a givenmarker obtained from a known diseased sample will be in the range ofdisease-associated measurements. As defined here, the clinical relevanceof the calculated sensitivity value represents an estimation of theprobability that a given marker would detect the presence of a clinicalcondition when applied to a subject with that condition.

As used herein, the “specificity” of a given marker refers to thepercentage of non-neoplastic samples that report a DNA methylation valuebelow a threshold value that distinguishes between neoplastic andnon-neoplastic samples. In some embodiments, a negative is defined as ahistology-confirmed non-neoplastic sample that reports a DNA methylationvalue below the threshold value (e.g., the range associated with nodisease) and a false positive is defined as a histology-confirmednon-neoplastic sample that reports a DNA methylation value above thethreshold value (e.g., the range associated with disease). The value ofspecificity, therefore, reflects the probability that a DNA methylationmeasurement for a given marker obtained from a known non-neoplasticsample will be in the range of non-disease associated measurements. Asdefined here, the clinical relevance of the calculated specificity valuerepresents an estimation of the probability that a given marker woulddetect the absence of a clinical condition when applied to a patientwithout that condition.

The term “AUC” as used herein is an abbreviation for the “area under acurve”. In particular it refers to the area under a Receiver OperatingCharacteristic (ROC) curve. The ROC curve is a plot of the true positiverate against the false positive rate for the different possible cutpoints of a diagnostic test. It shows the trade-off between sensitivityand specificity depending on the selected cut point (any increase insensitivity will be accompanied by a decrease in specificity). The areaunder an ROC curve (AUC) is a measure for the accuracy of a diagnostictest (the larger the area the better; the optimum is 1; a random testwould have a ROC curve lying on the diagonal with an area of 0.5; forreference: J. P. Egan. (1975) Signal Detection Theory and ROC Analysis,Academic Press, New York).

As used herein, the term “neoplasm” refers to “an abnormal mass oftissue, the growth of which exceeds and is uncoordinated with that ofthe normal tissues” See, e.g., Willis R A, “The Spread of Tumors in theHuman Body”, London, Butterworth & Co, 1952.

As used herein, the term “adenoma” refers to a benign tumor of glandularorigin. Although these growths are benign, over time they may progressto become malignant.

The term “pre-cancerous” or “pre-neoplastic” and equivalents thereofrefer to any cellular proliferative disorder that is undergoingmalignant transformation.

A “site” of a neoplasm, adenoma, cancer, etc. is the tissue, organ, celltype, anatomical area, body part, etc. in a subject's body where theneoplasm, adenoma, cancer, etc. is located.

As used herein, a “diagnostic” test application includes the detectionor identification of a disease state or condition of a subject,determining the likelihood that a subject will contract a given diseaseor condition, determining the likelihood that a subject with a diseaseor condition will respond to therapy, determining the prognosis of asubject with a disease or condition (or its likely progression orregression), and determining the effect of a treatment on a subject witha disease or condition. For example, a diagnostic can be used fordetecting the presence or likelihood of a subject contracting a neoplasmor the likelihood that such a subject will respond favorably to acompound (e.g., a pharmaceutical, e.g., a drug) or other treatment.

The term “marker”, as used herein, refers to a substance (e.g., anucleic acid or a region of a nucleic acid) that is able to diagnose acancer by distinguishing cancerous cells from normal cells, e.g., basedits methylation state.

The term “isolated” when used in relation to a nucleic acid, as in “anisolated oligonucleotide” refers to a nucleic acid sequence that isidentified and separated from at least one contaminant nucleic acid withwhich it is ordinarily associated in its natural source. Isolatednucleic acid is present in a form or setting that is different from thatin which it is found in nature. In contrast, non-isolated nucleic acids,such as DNA and RNA, are found in the state they exist in nature.Examples of non-isolated nucleic acids include: a given DNA sequence(e.g., a gene) found on the host cell chromosome in proximity toneighboring genes; RNA sequences, such as a specific mRNA sequenceencoding a specific protein, found in the cell as a mixture withnumerous other mRNAs which encode a multitude of proteins. However,isolated nucleic acid encoding a particular protein includes, by way ofexample, such nucleic acid in cells ordinarily expressing the protein,where the nucleic acid is in a chromosomal location different from thatof natural cells, or is otherwise flanked by a different nucleic acidsequence than that found in nature. The isolated nucleic acid oroligonucleotide may be present in single-stranded or double-strandedform. When an isolated nucleic acid or oligonucleotide is to be utilizedto express a protein, the oligonucleotide will contain at a minimum thesense or coding strand (i.e., the oligonucleotide may besingle-stranded), but may contain both the sense and anti-sense strands(i.e., the oligonucleotide may be double-stranded). An isolated nucleicacid may, after isolation from its natural or typical environment, by becombined with other nucleic acids or molecules. For example, an isolatednucleic acid may be present in a host cell in which into which it hasbeen placed, e.g., for heterologous expression.

The term “purified” refers to molecules, either nucleic acid or aminoacid sequences that are removed from their natural environment,isolated, or separated. An “isolated nucleic acid sequence” maytherefore be a purified nucleic acid sequence. “Substantially purified”molecules are at least 60% free, preferably at least 75% free, and morepreferably at least 90% free from other components with which they arenaturally associated. As used herein, the terms “purified” or “topurify” also refer to the removal of contaminants from a sample. Theremoval of contaminating proteins results in an increase in the percentof polypeptide or nucleic acid of interest in the sample. In anotherexample, recombinant polypeptides are expressed in plant, bacterial,yeast, or mammalian host cells and the polypeptides are purified by theremoval of host cell proteins; the percent of recombinant polypeptidesis thereby increased in the sample.

The term “composition comprising” a given polynucleotide sequence orpolypeptide refers broadly to any composition containing the givenpolynucleotide sequence or polypeptide. The composition may comprise anaqueous solution containing salts (e.g., NaCl), detergents (e.g., SDS),and other components (e.g., Denhardt's solution, dry milk, salmon spermDNA, etc.).

The term “sample” is used in its broadest sense. In one sense it canrefer to an animal cell or tissue. In another sense, it is meant toinclude a specimen or culture obtained from any source, as well asbiological and environmental samples. Biological samples may be obtainedfrom plants or animals (including humans) and encompass fluids, solids,tissues, and gases. Environmental samples include environmental materialsuch as surface matter, soil, water, and industrial samples. Theseexamples are not to be construed as limiting the sample types applicableto the present invention.

As used herein, a “remote sample” as used in some contexts relates to asample indirectly collected from a site that is not the cell, tissue, ororgan source of the sample. For instance, when sample materialoriginating from the colon or rectum is assessed in a stool sample(e.g., not from a sample taken directly from colorectal tissue), thesample is a remote sample.

As used herein, the terms “patient” or “subject” refer to organisms tobe subject to various tests provided by the technology. The term“subject” includes animals, preferably mammals, including humans. In apreferred embodiment, the subject is a primate. In an even morepreferred embodiment, the subject is a human.

As used herein, the term “kit” refers to any delivery system fordelivering materials. In the context of reaction assays, such deliverysystems include systems that allow for the storage, transport, ordelivery of reaction reagents (e.g., oligonucleotides, enzymes, etc. inthe appropriate containers) and/or supporting materials (e.g., buffers,written instructions for performing the assay etc.) from one location toanother. For example, kits include one or more enclosures (e.g., boxes)containing the relevant reaction reagents and/or supporting materials.As used herein, the term “fragmented kit” refers to delivery systemscomprising two or more separate containers that each contain asubportion of the total kit components. The containers may be deliveredto the intended recipient together or separately. For example, a firstcontainer may contain an enzyme for use in an assay, while a secondcontainer contains oligonucleotides. The term “fragmented kit” isintended to encompass kits containing Analyte specific reagents (ASR's)regulated under section 520(e) of the Federal Food, Drug, and CosmeticAct, but are not limited thereto. Indeed, any delivery system comprisingtwo or more separate containers that each contains a subportion of thetotal kit components are included in the term “fragmented kit.” Incontrast, a “combined kit” refers to a delivery system containing all ofthe components of a reaction assay in a single container (e.g., in asingle box housing each of the desired components). The term “kit”includes both fragmented and combined kits.

Embodiments of the Technology

In aggregate, gastrointestinal cancers account for more cancer mortalitythan any other organ system. Colorectal cancer (CRC) is the second mostfatal cancer, domestically, with >600,000 deaths annually. Whilecolorectal cancers are screened in the United State, compliance is poorgiven the cost, discomfort, and invasiveness of colonoscopy and thedismal performance of the current menu of non-invasive fecal bloodtests. To lessen the burden of CRC on individuals and society, newtesting strategies are needed which are both effective andpatient-friendly. A non-invasive, accurate molecular test utilizingbroadly informative biomarkers may provide a rational approach. A stoolbased assay is one such example. Colorectal cancers and pre-cancers shedcells and DNA into the digestive stream and are ultimately excreted instool. Highly sensitive assays have been used to detect both genetic andepigenetic markers in stools of patients with CRC cancer andprecancerous polyps. In a recent multicenter study, these markers wereincorporated into a stool assay that exhibited sensitivity for CRCessentially equivalent to that of colonoscopy. New markers would be ofincreased value if they proved to be more sensitive, more specific, ormore predictive of lesion site than existing markers. Furthermore,markers would ideally detect the critical precancerouslesions—adenomatous polyps and serrated polyps—in addition to CRC whenapplied to a screening application.

The genomic mechanisms underlying colorectal cancer involve gene andchromosomal abnormalities, including single base mutations, aneuploidy,deletions, translocations, copy number alterations, and expressionchanges. All of these events are being intensively studied using newergenomic technologies, including massively parallel sequencing. However,genetic alterations are proving to be very heterogeneous, and in somerespects random, rather than recurrent. The APC gene, for example, isthe most mutated gene in CRC lesions (˜90%), but the mutation sites arespread throughout 15 coding exons necessitating gene-wide analysis. Thisadds complexity to developing assays with the required performancelevels.

Epigenetic methylation of DNA at cytosine-phosphate-guanine (CpG) islandsites by DNA methyltransferases has been studied as a potential class ofbiomarkers in the tissues of most tumor types. In a biologicallyattractive mechanism, acquired methylation events in promotor regions oftumor suppressor genes are thought to silence expression, contributingto oncogenesis. DNA methylation may be a more chemically andbiologically stable diagnostic tool than RNA or protein expression.Furthermore, aberrant methylation markers are more broadly informativeand sensitive than are individual DNA mutations and offer excellentspecificity.

Clinical applications of highly discriminant markers could have greatimpact. For example, assay of such markers in distant media like stoolor blood find use in accurate screening or diagnostic assays fordetection of colorectal neoplasia.

In experiments conducted during the course of developing embodiments forthe present invention, markers were identified in a case-control studiesby comparing the methylation state of DNA markers from colorectal tissueof subjects with colorectal neoplasia, adenoma, and/or sessile serratedpolyps (SSP) to the methylation state of the same DNA markers fromcontrol subjects (e.g., normal tissue such as normal colon) (see,Examples 1-2, Tables 1-5).

For example, markers and/or panels of markers (e.g., a chromosomalregion having an annotation selected from FLI1, OPLAH, DTX1, MATK,SFMBT2 region 2, KCNK12, VAV3 region 1, SFMBT2 region 3, PPP2R5C, CHST2region 2, PKIA, PDGFD, ELOVL2, CHST2 region 1, SFMBT2 region 1, QKI,VAV3 region 2, and SLC8A3) were identified in a case-control study bycomparing the methylation state of DNA markers (e.g., from colorectaltissue of subjects with colorectal neoplasia and/or adenoma to themethylation state of the same DNA markers from control subjects (e.g.,normal tissue such as normal colon) (see, Example 1 and Tables 1A and1B).

Markers and/or panels of markers (e.g., a chromosomal region having anannotation selected from BMP3, NDRG4, PDGFG, CHST2, and SFMBT2) wereidentified in case-control studies by comparing the methylation state ofDNA markers from colorectal tissue of subjects having inflammatory boweldisease and colorectal cancer to the methylation state of the same DNAmarkers from control subjects (e.g., normal tissue such as normal colon)(see, Example 1 and Table 2).

In addition, 185, 244, and 111 DNA methylation markers specific forcolorectal cancers, large adenomas, and sessile serrated polyps,respectively, were identified (see, Example 2 and Tables 3, 4 and 5).Along with the colorectal cancer cases, large adenoma cases, and sessileserrated polyps cases, normal colonic mucosa, and normal white bloodcell DNA was sequenced.

Additional experiments conducted during the course of developingembodiments for the present invention demonstrated NDRG4, BMP3, OPLAH,FLI1, PDGFD, CHST_7889, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890,VAV3, and DTX1 as effective markers for detecting colorectal cancerwithin stool samples (see, Example 3 and Tables 6 and 7).

Accordingly, provided herein is technology for colorectal cancerscreening markers that provide a high signal-to-noise ratio and a lowbackground level when detected from samples taken from a subject (e.g.,stool sample; a colorectal tissue sample). Markers were identified in acase-control studies by comparing the methylation state of DNA markersfrom colorectal tissue of subjects with colorectal neoplasia and/oradenoma to the methylation state of the same DNA markers from controlsubjects (e.g., normal tissue such as normal colon) (see, Examples 1-3and Tables 1-6).

Although the disclosure herein refers to certain illustratedembodiments, it is to be understood that these embodiments are presentedby way of example and not by way of limitation.

In particular aspects, the present technology provides compositions andmethods for identifying, determining, and/or classifying a colorectalcancer. In some embodiments, the methods comprise determining themethylation status of at least one methylation marker in a biologicalsample isolated from a subject (e.g., a stool sample or a colorectaltissue sample), wherein a change in the methylation state of the markeris indicative of the presence, class, or site of a colorectal cancer.Particular embodiments relate to markers comprising a differentiallymethylated region (DMR, e.g., a DMR as provided in Tables 1-6) that areused for diagnosis or screening of neoplastic cellular proliferativedisorders (e.g., colorectal cancer), including early detection duringthe pre-cancerous stages of disease. Furthermore, the markers are usedfor the differentiation of neoplastic from benign cellular proliferativedisorders. In particular aspects, the present technology provides amethod wherein a neoplastic cell proliferative disorder is distinguishedfrom a benign cell proliferative disorder.

The markers of the present technology are particularly efficient indetecting or distinguishing between colorectal proliferative disorders,thereby providing improved means for the early detection,classification, and treatment of colorectal cancer.

In addition to embodiments wherein the methylation analysis of at leastone marker, a region of a marker, or a base of a marker comprising a DMR(e.g., a DMR as provided in Tables 1-6) provided herein is analyzed, thetechnology also provides panels of markers comprising at least onemarker, region of a marker, or base of a marker comprising a DMR withutility for the detection of colorectal cancers. In addition toembodiments wherein the methylation analysis of at least one marker, aregion of a marker, or a base of a marker comprising a DMR (e.g., a DMRas provided in Tables 1-6) provided herein is analyzed, the technologyalso provides panels of markers comprising any type or class of makers(e.g., complete marker, region of a marker, base of a marker, etc.)having utility for the detection of colorectal cancers (e.g., anexpression marker, amount of DNA, peptide, hemoglobin, etc.).

Some embodiments of the technology are based upon the analysis of theCpG methylation status of at least one marker, region of a marker, orbase of a marker comprising a DMR.

In some embodiments, the present technology provides for the use of abisulfite technique in combination with one or more methylation assaysto determine the methylation status of CpG dinucleotide sequences withinat least one marker comprising a DMR (e.g., a DMR as provided in Tables1-6). Genomic CpG dinucleotides can be methylated or unmethylated(alternatively known as up- and down-methylated respectively). Howeverthe methods of the present invention are suitable for the analysis ofbiological samples of a heterogeneous nature, e.g., a low concentrationof tumor cells, or biological materials therefrom, within a backgroundof a remote sample (e.g., blood, organ effluent, or stool). Accordingly,when analyzing the methylation status of a CpG position within such asample one may use a quantitative assay for determining the level (e.g.,percent, fraction, ratio, proportion, or degree) of methylation at aparticular CpG position.

Determination of the methylation status of CpG dinucleotide sequences inmarkers comprising a DMR has utility both in the diagnosis andcharacterization of colorectal cancers.

Combinations of Markers

In some embodiments, the technology relates to assessing the methylationstate of combinations of markers comprising a DMR from Tables 1-6 (e.g.,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,22, 23, 24, 25, 26, 27, 27, 29, 30) or more markers comprising a DMR. Insome embodiments, assessing the methylation state of more than onemarker increases the specificity and/or sensitivity of a screen ordiagnostic for identifying a colorectal neoplasm in a subject. Inaddition to embodiments wherein the methylation analysis of at least onemarker, a region of a marker, or a base of a marker comprising a DMR(e.g., a DMR as provided in Tables 1-6) provided herein is analyzed, thetechnology also provides panels of markers comprising any type or classof makers (e.g., complete marker, region of a marker, base of a marker,etc.) having utility for the detection of colorectal cancers (e.g., anexpression marker, amount of DNA, peptide, hemoglobin, etc.).

Various cancers are predicted by various combinations of markers, e.g.,as identified by statistical techniques related to specificity andsensitivity of prediction. The technology provides methods foridentifying predictive combinations and validated predictivecombinations for some cancers.

Methods for Assaying Methylation State

A method for analyzing a nucleic acid for the presence of5-methylcytosine is based upon the bisulfite method described byFrommer, et al. for the detection of 5-methylcytosines in DNA (Frommeret al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827-31) or variationsthereof. The bisulfite method of mapping 5-methylcytosines is based onthe observation that cytosine, but not 5-methylcytosine, reacts withhydrogen sulfite ion (also known as bisulfite). In some embodiments, thereaction is performed according to the following steps: first, cytosinereacts with hydrogen sulfite to form a sulfonated cytosine. Next,spontaneous deamination of the sulfonated reaction intermediate resultsin a sulfonated uracil. Finally, the sulfonated uricil is desulfonatedunder alkaline conditions to form uracil. Detection is possible becauseuracil forms base pairs with adenine (thus behaving like thymine),whereas 5-methylcytosine base pairs with guanine (thus behaving likecytosine). This makes the discrimination of methylated cytosines fromnon-methylated cytosines possible by, e.g., bisulfite genomic sequencing(Grigg G, & Clark S, Bioessays (1994) 16: 431-36; Grigg G, DNA Seq.(1996) 6: 189-98) or methylation-specific PCR (MSP) as is disclosed,e.g., in U.S. Pat. No. 5,786,146.

Some conventional technologies are related to methods comprisingenclosing the DNA to be analyzed in an agarose matrix, therebypreventing the diffusion and renaturation of the DNA (bisulfite onlyreacts with single-stranded DNA), and replacing precipitation andpurification steps with a fast dialysis (Olek A, et al. (1996) “Amodified and improved method for bisulfite based cytosine methylationanalysis” Nucleic Acids Res. 24: 5064-6). It is thus possible to analyzeindividual cells for methylation status, illustrating the utility andsensitivity of the method. An overview of conventional methods fordetecting 5-methylcytosine is provided by Rein, T., et al. (1998)Nucleic Acids Res. 26: 2255.

The bisulfite technique typically involves amplifying short, specificfragments of a known nucleic acid subsequent to a bisulfite treatment,then either assaying the product by sequencing (Olek & Walter (1997)Nat. Genet. 17: 275-6) or a primer extension reaction (Gonzalgo & Jones(1997) Nucleic Acids Res. 25: 2529-31; WO 95/00669; U.S. Pat. No.6,251,594) to analyze individual cytosine positions. Some methods useenzymatic digestion (Xiong & Laird (1997) Nucleic Acids Res. 25:2532-4). Detection by hybridization has also been described in the art(Olek et al., WO 99/28498). Additionally, use of the bisulfite techniquefor methylation detection with respect to individual genes has beendescribed (Grigg & Clark (1994) Bioessays 16: 431-6; Zeschnigk et al.(1997) Hum Mol Genet. 6: 387-95; Feil et al. (1994) Nucleic Acids Res.22: 695; Martin et al. (1995) Gene 157: 261-4; WO 9746705; WO 9515373).

Various methylation assay procedures are known in the art and can beused in conjunction with bisulfite treatment according to the presenttechnology. These assays allow for determination of the methylationstate of one or a plurality of CpG dinucleotides (e.g., CpG islands)within a nucleic acid sequence. Such assays involve, among othertechniques, sequencing of bisulfite-treated nucleic acid, PCR (forsequence-specific amplification), Southern blot analysis, and use ofmethylation-sensitive restriction enzymes.

For example, genomic sequencing has been simplified for analysis ofmethylation patterns and 5-methylcytosine distributions by usingbisulfite treatment (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA89: 1827-1831). Additionally, restriction enzyme digestion of PCRproducts amplified from bisulfite-converted DNA finds use in assessingmethylation state, e.g., as described by Sadri & Hornsby (1997) Nucl.Acids Res. 24: 5058-5059 or as embodied in the method known as COBRA(Combined Bisulfite Restriction Analysis) (Xiong & Laird (1997) NucleicAcids Res. 25: 2532-2534).

COBRA™ analysis is a quantitative methylation assay useful fordetermining DNA methylation levels at specific loci in small amounts ofgenomic DNA (Xiong & Laird, Nucleic Acids Res. 25:2532-2534, 1997).Briefly, restriction enzyme digestion is used to revealmethylation-dependent sequence differences in PCR products of sodiumbisulfite-treated DNA. Methylation-dependent sequence differences arefirst introduced into the genomic DNA by standard bisulfite treatmentaccording to the procedure described by Frommer et al. (Proc. Natl.Acad. Sci. USA 89:1827-1831, 1992). PCR amplification of the bisulfiteconverted DNA is then performed using primers specific for the CpGislands of interest, followed by restriction endonuclease digestion, gelelectrophoresis, and detection using specific, labeled hybridizationprobes. Methylation levels in the original DNA sample are represented bythe relative amounts of digested and undigested PCR product in alinearly quantitative fashion across a wide spectrum of DNA methylationlevels. In addition, this technique can be reliably applied to DNAobtained from microdissected paraffin-embedded tissue samples.

Typical reagents (e.g., as might be found in a typical COBRA™-based kit)for COBRA™ analysis may include, but are not limited to: PCR primers forspecific loci (e.g., specific genes, markers, DMR, regions of genes,regions of markers, bisulfite treated DNA sequence, CpG island, etc.);restriction enzyme and appropriate buffer; gene-hybridizationoligonucleotide; control hybridization oligonucleotide; kinase labelingkit for oligonucleotide probe; and labeled nucleotides. Additionally,bisulfite conversion reagents may include: DNA denaturation buffer;sulfonation buffer; DNA recovery reagents or kits (e.g., precipitation,ultrafiltration, affinity column); desulfonation buffer; and DNArecovery components.

Preferably, assays such as “MethyLight™” (a fluorescence-based real-timePCR technique) (Eads et al., Cancer Res. 59:2302-2306, 1999), Ms-SNuPE™(Methylation-sensitive Single Nucleotide Primer Extension) reactions(Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997),methylation-specific PCR (“MSP”; Herman et al., Proc. Natl. Acad. Sci.USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146), and methylated CpGisland amplification (“MCA”; Toyota et al., Cancer Res. 59:2307-12,1999) are used alone or in combination with one or more of thesemethods.

The “HeavyMethyl™” assay, technique is a quantitative method forassessing methylation differences based on methylation-specificamplification of bisulfite-treated DNA. Methylation-specific blockingprobes (“blockers”) covering CpG positions between, or covered by, theamplification primers enable methylation-specific selectiveamplification of a nucleic acid sample.

The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™MethyLight™ assay, which is a variation of the MethyLight™ assay,wherein the MethyLight™ assay is combined with methylation specificblocking probes covering CpG positions between the amplificationprimers. The HeavyMethyl™ assay may also be used in combination withmethylation specific amplification primers.

Typical reagents (e.g., as might be found in a typical MethyLight™-basedkit) for HeavyMethyl™ analysis may include, but are not limited to: PCRprimers for specific loci (e.g., specific genes, markers, DMR, regionsof genes, regions of markers, bisulfite treated DNA sequence, CpGisland, or bisulfite treated DNA sequence or CpG island, etc.); blockingoligonucleotides; optimized PCR buffers and deoxynucleotides; and Taqpolymerase.

MSP (methylation-specific PCR) allows for assessing the methylationstatus of virtually any group of CpG sites within a CpG island,independent of the use of methylation-sensitive restriction enzymes(Herman et al. Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat.No. 5,786,146). Briefly, DNA is modified by sodium bisulfite, whichconverts unmethylated, but not methylated cytosines, to uracil, and theproducts are subsequently amplified with primers specific for methylatedversus unmethylated DNA. MSP requires only small quantities of DNA, issensitive to 0.1% methylated alleles of a given CpG island locus, andcan be performed on DNA extracted from paraffin-embedded samples.Typical reagents (e.g., as might be found in a typical MSP-based kit)for MSP analysis may include, but are not limited to: methylated andunmethylated PCR primers for specific loci (e.g., specific genes,markers, DMR, regions of genes, regions of markers, bisulfite treatedDNA sequence, CpG island, etc.); optimized PCR buffers anddeoxynucleotides, and specific probes.

The MethyLight™ assay is a high-throughput quantitative methylationassay that utilizes fluorescence-based real-time PCR (e.g., TaqMan®)that requires no further manipulations after the PCR step (Eads et al.,Cancer Res. 59:2302-2306, 1999). Briefly, the MethyLight™ process beginswith a mixed sample of genomic DNA that is converted, in a sodiumbisulfite reaction, to a mixed pool of methylation-dependent sequencedifferences according to standard procedures (the bisulfite processconverts unmethylated cytosine residues to uracil). Fluorescence-basedPCR is then performed in a “biased” reaction, e.g., with PCR primersthat overlap known CpG dinucleotides. Sequence discrimination occursboth at the level of the amplification process and at the level of thefluorescence detection process.

The MethyLight™ assay is used as a quantitative test for methylationpatterns in a nucleic acid, e.g., a genomic DNA sample, wherein sequencediscrimination occurs at the level of probe hybridization. In aquantitative version, the PCR reaction provides for a methylationspecific amplification in the presence of a fluorescent probe thatoverlaps a particular putative methylation site. An unbiased control forthe amount of input DNA is provided by a reaction in which neither theprimers, nor the probe, overlie any CpG dinucleotides. Alternatively, aqualitative test for genomic methylation is achieved by probing thebiased PCR pool with either control oligonucleotides that do not coverknown methylation sites (e.g., a fluorescence-based version of theHeavyMethyl™ and MSP techniques) or with oligonucleotides coveringpotential methylation sites.

The MethyLight™ process is used with any suitable probe (e.g. a“TaqMan®” probe, a Lightcycler® probe, etc.) For example, in someapplications double-stranded genomic DNA is treated with sodiumbisulfite and subjected to one of two sets of PCR reactions usingTaqMan® probes, e.g., with MSP primers and/or HeavyMethyl blockeroligonucleotides and a TaqMan® probe. The TaqMan® probe is dual-labeledwith fluorescent “reporter” and “quencher” molecules and is designed tobe specific for a relatively high GC content region so that it melts atabout a 10° C. higher temperature in the PCR cycle than the forward orreverse primers. This allows the TaqMan® probe to remain fullyhybridized during the PCR annealing/extension step. As the Taqpolymerase enzymatically synthesizes a new strand during PCR, it willeventually reach the annealed TaqMan® probe. The Taq polymerase 5′ to 3′endonuclease activity will then displace the TaqMan® probe by digestingit to release the fluorescent reporter molecule for quantitativedetection of its now unquenched signal using a real-time fluorescentdetection system.

Typical reagents (e.g., as might be found in a typical MethyLight™-basedkit) for MethyLight™ analysis may include, but are not limited to: PCRprimers for specific loci (e.g., specific genes, markers, DMR, regionsof genes, regions of markers, bisulfite treated DNA sequence, CpGisland, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers anddeoxynucleotides; and Taq polymerase.

The QM™ (quantitative methylation) assay is an alternative quantitativetest for methylation patterns in genomic DNA samples, wherein sequencediscrimination occurs at the level of probe hybridization. In thisquantitative version, the PCR reaction provides for unbiasedamplification in the presence of a fluorescent probe that overlaps aparticular putative methylation site. An unbiased control for the amountof input DNA is provided by a reaction in which neither the primers, northe probe, overlie any CpG dinucleotides. Alternatively, a qualitativetest for genomic methylation is achieved by probing the biased PCR poolwith either control oligonucleotides that do not cover known methylationsites (a fluorescence-based version of the HeavyMethyl™ and MSPtechniques) or with oligonucleotides covering potential methylationsites.

The QM™ process can by used with any suitable probe, e.g., “TaqMan®”probes, Lightcycler® probes, in the amplification process. For example,double-stranded genomic DNA is treated with sodium bisulfite andsubjected to unbiased primers and the TaqMan® probe. The TaqMan® probeis dual-labeled with fluorescent “reporter” and “quencher” molecules,and is designed to be specific for a relatively high GC content regionso that it melts out at about a 10° C. higher temperature in the PCRcycle than the forward or reverse primers. This allows the TaqMan® probeto remain fully hybridized during the PCR annealing/extension step. Asthe Taq polymerase enzymatically synthesizes a new strand during PCR, itwill eventually reach the annealed TaqMan® probe. The Taq polymerase 5′to 3′ endonuclease activity will then displace the TaqMan® probe bydigesting it to release the fluorescent reporter molecule forquantitative detection of its now unquenched signal using a real-timefluorescent detection system. Typical reagents (e.g., as might be foundin a typical QM™-based kit) for QM™ analysis may include, but are notlimited to: PCR primers for specific loci (e.g., specific genes,markers, DMR, regions of genes, regions of markers, bisulfite treatedDNA sequence, CpG island, etc.); TaqMan® or Lightcycler® probes;optimized PCR buffers and deoxynucleotides; and Taq polymerase.

The Ms-SNuPE™ technique is a quantitative method for assessingmethylation differences at specific CpG sites based on bisulfitetreatment of DNA, followed by single-nucleotide primer extension(Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997). Briefly,genomic DNA is reacted with sodium bisulfite to convert unmethylatedcytosine to uracil while leaving 5-methylcytosine unchanged.Amplification of the desired target sequence is then performed using PCRprimers specific for bisulfite-converted DNA, and the resulting productis isolated and used as a template for methylation analysis at the CpGsite of interest. Small amounts of DNA can be analyzed (e.g.,microdissected pathology sections) and it avoids utilization ofrestriction enzymes for determining the methylation status at CpG sites.

Typical reagents (e.g., as might be found in a typical Ms-SNuPE™-basedkit) for Ms-SNuPE™ analysis may include, but are not limited to: PCRprimers for specific loci (e.g., specific genes, markers, DMR, regionsof genes, regions of markers, bisulfite treated DNA sequence, CpGisland, etc.); optimized PCR buffers and deoxynucleotides; gelextraction kit; positive control primers; Ms-SNuPE™ primers for specificloci; reaction buffer (for the Ms-SNuPE reaction); and labelednucleotides. Additionally, bisulfite conversion reagents may include:DNA denaturation buffer; sulfonation buffer; DNA recovery reagents orkit (e.g., precipitation, ultrafiltration, affinity column);desulfonation buffer; and DNA recovery components.

Reduced Representation Bisulfite Sequencing (RRBS) begins with bisulfitetreatment of nucleic acid to convert all unmethylated cytosines touracil, followed by restriction enzyme digestion (e.g., by an enzymethat recognizes a site including a CG sequence such as MspI) andcomplete sequencing of fragments after coupling to an adapter ligand.The choice of restriction enzyme enriches the fragments for CpG denseregions, reducing the number of redundant sequences that may map tomultiple gene positions during analysis. As such, RRBS reduces thecomplexity of the nucleic acid sample by selecting a subset (e.g., bysize selection using preparative gel electrophoresis) of restrictionfragments for sequencing. As opposed to whole-genome bisulfitesequencing, every fragment produced by the restriction enzyme digestioncontains DNA methylation information for at least one CpG dinucleotide.As such, RRBS enriches the sample for promoters, CpG islands, and othergenomic features with a high frequency of restriction enzyme cut sitesin these regions and thus provides an assay to assess the methylationstate of one or more genomic loci.

A typical protocol for RRBS comprises the steps of digesting a nucleicacid sample with a restriction enzyme such as MspI, filling in overhangsand A-tailing, ligating adaptors, bisulfite conversion, and PCR. See,e.g., et al. (2005) Nat Methods 7: 133-6; Meissner et al. (2005) NucleicAcids Res. 33: 5868-77.

In some embodiments, a quantitative allele-specific real-time target andsignal amplification (QuARTS) assay is used to evaluate methylationstate. Three reactions sequentially occur in each QuARTS assay,including amplification (reaction 1) and target probe cleavage (reaction2) in the primary reaction; and FRET cleavage and fluorescent signalgeneration (reaction 3) in the secondary reaction. When target nucleicacid is amplified with specific primers, a specific detection probe witha flap sequence loosely binds to the amplicon. The presence of thespecific invasive oligonucleotide at the target binding site causescleavase to release the flap sequence by cutting between the detectionprobe and the flap sequence. The flap sequence is complementary to anonhairpin portion of a corresponding FRET cassette. Accordingly, theflap sequence functions as an invasive oligonucleotide on the FRETcassette and effects a cleavage between the FRET cassette fluorophoreand a quencher, which produces a fluorescent signal. The cleavagereaction can cut multiple probes per target and thus release multiplefluorophore per flap, providing exponential signal amplification. QuARTScan detect multiple targets in a single reaction well by using FRETcassettes with different dyes. See, e.g., in Zou et al. (2010)“Sensitive quantification of methylated markers with a novel methylationspecific technology” Clin Chem 56: A199; U.S. Pat. No. 8,361,720 andU.S. patent application Ser. Nos. 13/594,674, 12/946,745, and12/946,752.

In some embodiments, target nucleic acid is isolated from a samplethrough, for example, a direct gene capture. For example, in someembodiments, target nucleic acid is isolated from a sample through, forexample, removal of assay inhibiting agents to produce a clarifiedsample (e.g., with PVP, PVPP and/or the use of a spin filter), captureof a target nucleic acid (if present) from the clarified sample with acapture reagent to form a capture complex, isolating the capture complexfrom the clarified sample, recovering the target nucleic acid (ifpresent) from the capture complex in a nucleic acid solution, andoptionally repeating for isolation of different targets (see, e.g., U.S.patent application Ser. Nos. 14/145,082, 14/145,087, 14/145,070,14/145,056, 13/470,251, 13/470,018, 13/469,999 and 13/469,989).

In some embodiments, fragments of the treated DNA are amplified usingsets of primer oligonucleotides according to the present invention(e.g., see Table 2) and an amplification enzyme. The amplification ofseveral DNA segments can be carried out simultaneously in one and thesame reaction vessel. Typically, the amplification is carried out usinga polymerase chain reaction (PCR). Amplicons are typically 100 to 2000base pairs in length.

In another embodiment of the method, the methylation status of CpGpositions within or near a marker comprising a DMR (e.g., a DMR asprovided in Tables 1-6) may be detected by use of methylation-specificprimer oligonucleotides. This technique (MSP) has been described in U.S.Pat. No. 6,265,171 to Herman. The use of methylation status specificprimers for the amplification of bisulfite treated DNA allows thedifferentiation between methylated and unmethylated nucleic acids. MSPprimer pairs contain at least one primer that hybridizes to a bisulfitetreated CpG dinucleotide. Therefore, the sequence of said primerscomprises at least one CpG dinucleotide. MSP primers specific fornon-methylated DNA contain a “T” at the position of the C position inthe CpG.

The fragments obtained by means of the amplification can carry adirectly or indirectly detectable label. In some embodiments, the labelsare fluorescent labels, radionuclides, or detachable molecule fragmentshaving a typical mass that can be detected in a mass spectrometer. Wheresaid labels are mass labels, some embodiments provide that the labeledamplicons have a single positive or negative net charge, allowing forbetter delectability in the mass spectrometer. The detection may becarried out and visualized by means of, e.g., matrix assisted laserdesorption/ionization mass spectrometry (MALDI) or using electron spraymass spectrometry (ESI).

In some embodiments, methods for isolating DNA comprise isolation ofnucleic acids as described in U.S. patent application Ser. No.13/470,251 (“Isolation of Nucleic Acids”).

Methods

In some embodiments the technology, methods are provided that comprisethe following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated        from a body fluids such as a stool sample or colorectal tissue)        obtained from the subject with at least one reagent or series of        reagents that distinguishes between methylated and        non-methylated CpG dinucleotides within at least one marker DMR        (e.g., a DMR as provided in Tables 1-6) and    -   2) detecting a colorectal neoplasm or proliferative disorder        (e.g., colorectal cancer, large adenoma, SSP) (e.g., afforded        with a sensitivity of greater than or equal to 80% and a        specificity of greater than or equal to 80%).

In some embodiments the technology, methods are provided that comprisethe following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated        from a body fluids such as a stool sample or colorectal tissue)        obtained from the subject with at least one reagent or series of        reagents that distinguishes between methylated and        non-methylated CpG dinucleotides within at least one marker        selected from a chromosomal region having an annotation selected        from the group consisting of BMP3, NDRG4, FLI1, OPLAH, DTX1,        MATK, SFMBT2 region 2, KCNK12, VAV3 region 1, SFMBT2 region 3,        PPP2R5C, CHST2 region 2, PKIA, PDGFD, ELOVL2, CHST2 region 1,        SFMBT2 region 1, QKI, VAV3 region 2, and SLC8A3, and    -   2) detecting colorectal cancer (e.g., afforded with a        sensitivity of greater than or equal to 80% and a specificity of        greater than or equal to 80%).        Preferably, the sensitivity is from about 70% to about 100%, or        from about 80% to about 90%, or from about 80% to about 85%. In        some embodiments, the specificity is from about 70% to about        100%, or from about 80% to about 90%, or from about 80% to about        85%. In some embodiments, the specificity is from about 90% to        100%, 91% to 99%, 93% to 97%, 94% to 96%, 95% to 99%, 96% to        99.5%, 97% to 99.9%, etc.).

Genomic DNA may be isolated by any means, including the use ofcommercially available kits. Briefly, wherein the DNA of interest isencapsulated by a cellular membrane the biological sample should bedisrupted and lysed by enzymatic, chemical or mechanical means. The DNAsolution may then be cleared of proteins and other contaminants, e.g.,by digestion with proteinase K. The genomic DNA is then recovered fromthe solution. This may be carried out by means of a variety of methodsincluding salting out, organic extraction, or binding of the DNA to asolid phase support. The choice of method will be affected by severalfactors including time, expense, and required quantity of DNA. Allsample types comprising neoplastic matter or pre-neoplastic matter aresuitable for use in the present method, e.g., cell lines, histologicalslides, biopsies, paraffin-embedded tissue, body fluids, stool, coloniceffluent, urine, blood plasma, blood serum, whole blood, isolated bloodcells, cells isolated from the blood, and combinations thereof.

The technology is not limited in the methods used to prepare the samplesand provide a nucleic acid for testing. For example, in someembodiments, a DNA is isolated from a stool sample or from blood or froma plasma sample using direct gene capture, e.g., as detailed in U.S.patent application Ser. Nos. 14/145,082, 14/145,087, 14/145,070,14/145,056, 13/470,251, 13/470,018, 13/469,999 and 13/469,989.

The genomic DNA sample is then treated with at least one reagent, orseries of reagents, that distinguishes between methylated andnon-methylated CpG dinucleotides within at least one marker comprising aDMR (e.g., a DMR as provided in Tables 1-6).

In some embodiments, the reagent converts cytosine bases which areunmethylated at the 5′-position to uracil, thymine, or another basewhich is dissimilar to cytosine in terms of hybridization behavior.However in some embodiments, the reagent may be a methylation sensitiverestriction enzyme.

In some embodiments, the genomic DNA sample is treated in such a mannerthat cytosine bases that are unmethylated at the 5′ position areconverted to uracil, thymine, or another base that is dissimilar tocytosine in terms of hybridization behavior. In some embodiments, thistreatment is carried out with bisulfate (hydrogen sulfite, disulfite)followed by alkaline hydrolysis.

The treated nucleic acid is then analyzed to determine the methylationstate of the target gene sequences (at least one gene, genomic sequence,or nucleotide from a marker comprising a DMR, e.g., at least one DMR asprovided in Tables 1-6). In some embodiments, the method of analysis isQuARTS and/or MSP as described herein.

Aberrant methylation, more specifically hypermethylation of a markercomprising a DMR (e.g., a DMR as provided in Tables 1-6) is associatedwith a colorectal cancer.

The technology relates to the analysis of any sample associated with acolorectal cancer. For example, in some embodiments the sample comprisesa tissue and/or biological fluid obtained from a patient. In someembodiments, the sample comprises a secretion. In some embodiments, thesample comprises blood, serum, plasma, gastric secretions, colorectaltissue, colorectal tumor tissue, a colorectal biopsy sample, pancreaticjuice, a gastrointestinal biopsy sample, microdissected cells from agastrointestinal biopsy, gastrointestinal cells sloughed into thegastrointestinal lumen, and/or gastrointestinal cells recovered fromstool. In some embodiments, the subject is human. These samples mayoriginate from the upper gastrointestinal tract, the lowergastrointestinal tract, or comprise cells, tissues, and/or secretionsfrom both the upper gastrointestinal tract and the lowergastrointestinal tract. The sample may include cells, secretions, ortissues from the liver, bile ducts, pancreas, stomach, colon, rectum,esophagus, small intestine, appendix, duodenum, polyps, gall bladder,anus, and/or peritoneum. In some embodiments, the sample comprisescellular fluid, ascites, urine, feces, pancreatic fluid, fluid obtainedduring endoscopy, blood, mucus, or saliva. In some embodiments, thesample is a stool sample.

Such samples can be obtained by any variety of techniques. For instance,urine and fecal samples are readily attainable, while blood, ascites,serum, colorectal, or pancreatic fluid samples can be obtainedparenterally by using a needle and syringe, for instance. Cell free orsubstantially cell free samples can be obtained by subjecting the sampleto various techniques including, but not limited to, centrifugation andfiltration. Although it is generally preferred that no invasivetechniques are used to obtain the sample, it still may be preferable toobtain samples such as tissue homogenates, tissue sections, and biopsyspecimens

In some embodiments, the technology provides a method for treating apatient (e.g., a patient with colorectal cancer, with early stagecolorectal cancer, or who may develop colorectal cancer), the methodcomprising determining the methylation state of one or more DMR asprovided herein and administering a treatment to the patient based onthe results of determining the methylation state. The treatment may beconducting a colonoscopy, administration of a pharmaceutical compound, avaccine, performing a surgery, imaging the patient, performing anothertest. Preferably, said use is in a method of clinical screening, amethod of prognosis assessment, a method of monitoring the results oftherapy, a method to identify patients most likely to respond to aparticular therapeutic treatment, a method of imaging a patient orsubject, and a method for drug screening and development.

In some embodiments, clinical cancer prognosis includes determining theaggressiveness of the cancer and the likelihood of tumor recurrence toplan the most effective therapy. If a more accurate prognosis can bemade or even a potential risk for developing the cancer can be assessed,appropriate therapy, and in some instances less severe therapy for thepatient can be chosen. Assessment (e.g., determining methylation state)of cancer biomarkers is useful to separate subjects with good prognosisand/or low risk of developing cancer who will need no therapy or limitedtherapy from those more likely to develop cancer or suffer a recurrenceof cancer who might benefit from more intensive treatments ormonitoring.

In some embodiments of the presently disclosed subject matter, multipledetermination of the biomarkers over time are made to facilitatediagnosis and/or prognosis. A temporal change in the biomarker is usedto predict a clinical outcome, monitor the progression ofgastrointestinal cancer, and/or monitor the efficacy of appropriatetherapies directed against the cancer. In such an embodiment forexample, one might expect to see a change in the methylation state ofone or more biomarkers (e.g., DMR) disclosed herein (and potentially oneor more additional biomarker(s), if monitored) in a biological sampleover time during the course of an effective therapy.

In some embodiments, the methods and compositions of the invention areemployed for treatment or diagnosis of disease at an early stage, forexample, before symptoms of the disease appear.

In some embodiments, a statistical analysis associates a prognosticindicator with a predisposition to an adverse outcome. For example, insome embodiments, a methylation state different from that in a normalcontrol sample obtained from a patient who does not have a cancer cansignal that a subject is more likely to suffer from a cancer thansubjects with a level that is more similar to the methylation state inthe control sample, as determined by a level of statisticalsignificance. Additionally, a change in methylation state from abaseline (e.g., “normal”) level can be reflective of subject prognosis,and the degree of change in methylation state can be related to theseverity of adverse events. Statistical significance is often determinedby comparing two or more populations and determining a confidenceinterval and/or a p value. See, e.g., Dowdy and Wearden, Statistics forResearch, John Wiley & Sons, New York, 1983. Exemplary confidenceintervals of the present subject matter are 90%, 95%, 97.5%, 98%, 99%,99.5%, 99.9% and 99.99%, while exemplary p values are 0.1, 0.05, 0.025,0.02, 0.01, 0.005, 0.001, and 0.0001.

In other embodiments, a threshold degree of change in the methylationstate of a prognostic or diagnostic biomarker disclosed herein (e.g., aDMR) can be established, and the degree of change in the methylationstate of the biamarker in a biological sample is simply compared to thethreshold degree of change in the methylation state. A preferredthreshold change in the methylation state for biomarkers provided hereinis about 5%, about 10%, about 15%, about 20%, about 25%, about 30%,about 50%, about 75%, about 100%, and about 150%. In yet otherembodiments, a “nomogram” can be established, by which a methylationstate of a prognostic or diagnostic indicator (biomarker or combinationof biomarkers) is directly related to an associated disposition towardsa given outcome. The skilled artisan is acquainted with the use of suchnomograms to relate two numeric values with the understanding that theuncertainty in this measurement is the same as the uncertainty in themarker concentration because individual sample measurements arereferenced, not population averages.

In some embodiments, a control sample is analyzed concurrently with thebiological sample, such that the results obtained from the biologicalsample can be compared to the results obtained from the control sample.Additionally, it is contemplated that standard curves can be provided,with which assay results for the biological sample may be compared. Suchstandard curves present methylation states of a biomarker as a functionof assay units, e.g., fluorescent signal intensity, if a fluorescentlabel is used. Using samples taken from multiple donors, standard curvescan be provided for control methylation states of the one or morebiomarkers in normal tissue, as well as for “at-risk” levels of the oneor more biomarkers in tissue taken from donors with metaplasia or fromdonors with a gastrointestinal cancer. In certain embodiments of themethod, a subject is identified as having metaplasia upon identifying anaberrant methylation state of one or more DMR provided herein in abiological sample obtained from the subject. In other embodiments of themethod, the detection of an aberrant methylation state of one or more ofsuch biomarkers in a biological sample obtained from the subject resultsin the subject being identified as having cancer.

The analysis of markers can be carried out separately or simultaneouslywith additional markers within one test sample. For example, severalmarkers can be combined into one test for efficient processing of amultiple of samples and for potentially providing greater diagnosticand/or prognostic accuracy. In addition, one skilled in the art wouldrecognize the value of testing multiple samples (for example, atsuccessive time points) from the same subject. Such testing of serialsamples can allow the identification of changes in marker methylationstates over time. Changes in methylation state, as well as the absenceof change in methylation state, can provide useful information about thedisease status that includes, but is not limited to, identifying theapproximate time from onset of the event, the presence and amount ofsalvageable tissue, the appropriateness of drug therapies, theeffectiveness of various therapies, and identification of the subject'soutcome, including risk of future events.

The analysis of biomarkers can be carried out in a variety of physicalformats. For example, the use of microtiter plates or automation can beused to facilitate the processing of large numbers of test samples.Alternatively, single sample formats may be used to facilitate immediatetreatment and diagnosis in a timely fashion, for example, in ambulatorytransport or emergency room settings.

In some embodiments, the subject is diagnosed as having a colorectalcancer if, when compared to a control methylation state, there is ameasurable difference in the methylation state of at least one biomarkerin the sample. Conversely, when no change in methylation state isidentified in the biological sample, the subject can be identified asnot having colorectal cancer, not being at risk for the cancer, or ashaving a low risk of the cancer. In this regard, subjects having thecancer or risk thereof can be differentiated from subjects having low tosubstantially no cancer or risk thereof. Those subjects having a risk ofdeveloping a colorectal cancer can be placed on a more intensive and/orregular screening schedule, including endoscopic surveillance. On theother hand, those subjects having low to substantially no risk may avoidbeing subjected to an endoscopy, until such time as a future screening,for example, a screening conducted in accordance with the presenttechnology, indicates that a risk of colorectal cancer has appeared inthose subjects.

As mentioned above, depending on the embodiment of the method of thepresent technology, detecting a change in methylation state of the oneor more biomarkers can be a qualitative determination or it can be aquantitative determination. As such, the step of diagnosing a subject ashaving, or at risk of developing, a gastrointestinal cancer indicatesthat certain threshold measurements are made, e.g., the methylationstate of the one or more biomarkers in the biological sample varies froma predetermined control methylation state. In some embodiments of themethod, the control methylation state is any detectable methylationstate of the biomarker. In other embodiments of the method where acontrol sample is tested concurrently with the biological sample, thepredetermined methylation state is the methylation state in the controlsample. In other embodiments of the method, the predeterminedmethylation state is based upon and/or identified by a standard curve.In other embodiments of the method, the predetermined methylation stateis a specifically state or range of state. As such, the predeterminedmethylation state can be chosen, within acceptable limits that will beapparent to those skilled in the art, based in part on the embodiment ofthe method being practiced and the desired specificity, etc.

The presently-disclosed subject matter further includes a system fordiagnosing a gastrointestinal cancer in a subject. The system can beprovided, for example, as a commercial kit that can be used to screenfor a risk of gastrointestinal cancer or diagnose a gastrointestinalcancer in a subject from whom a biological sample has been collected. Anexemplary system provided in accordance with the present technologyincludes assessing the methylation state of a DMR as provided in Tables1-6.

EXAMPLES Example 1

This example describes independent case-control tissue studies whichidentified highly discriminant methylation markers for colorectalneoplasia. The examples used RRBS for the discovery phase andmethylation-specific PCR (MSP) and quantitative allele-specificreal-time target and signal amplification (QuARTs) for the validationphase.

Tissue samples were identified from existing cancer registries. Theaccessible population included those who underwent either open orlaparoscopic colectomy, or colon biopsy with an archived specimen. Alltissues were reviewed by an expert gastrointestinal pathologist toconfirm correct classification. Colorectal neoplasia case tissuesincluded stages I-IV colorectal cancers (fresh-frozen), advancedadenomas >1 cm in size (fresh-frozen), and right-sided sessile serratedpolyps (FFPE). There were two control groups studied. The first controlgroup included 18 colonic epithelial tissues from patients confirmed tobe free from colonic neoplasm. The second group included 18 normal buffycoat samples from cancer free patients. Cases and both controls werematched by sex and age. In addition, the CRC and advanced adenomacohorts were evenly distributed between right and left sided lesions. Ina central core laboratory, case and control tissues were micro-dissectedand DNA was extracted using a phenol-chloroform technique, yielding atleast 500 ng of DNA. Case identification, matching and DNA extractionwere performed by independent personnel to maintain blinding oflaboratory personnel to case and control status.

Genomic DNA (300 ng) was fragmented by digestion with 10 Units of MspI,a methylation-specific restriction enzyme which recognizes CpGcontaining motifs. This enriches the samples for CpG content andeliminates redundant areas of the genome. Digested fragments wereend-repaired and A-tailed with 5 Units of Klenow fragment (3′-5′ exo-),and ligated overnight to methylated TruSeq adapters (Illumina, San DiegoCalif.) containing one of four barcode sequences (to link each fragmentto its sample ID.) Size selection of 160-340 bp fragments (40-220 bpinserts) was performed using Agencourt AMPure XP SPRI beads/buffer(Beckman Coulter, Brea Calif.). Buffer cutoffs were 0.7× to 1.1× samplevolumes of beads/buffer. Final elution volume was 22 uL (EBbuffer—Qiagen, Germantown Md.) qPCR was used to gauge ligationefficiency and fragment quality on a small aliquot of sample. Samplesthen underwent bisulfite conversion (twice) using a modified EpiTectprotocol (Qiagen). qPCR and conventional PCR (PfuTurbo Cxhotstart—Agilent, Santa Clara Calif.) followed by Bioanalyzer 2100(Agilent) assessment on converted sample aliquots determined the optimalPCR cycle number prior to amplification of the final library. Conditionsfor final PCR: 50 uL r×n: 5 uL of 10× buffer, 1.25 uL of 10 mM eachdNTP's, 5 uL primer cocktail (˜5 uM), 15 uL template (sample), 1 uLPfuTurbo Cx hotstart, 22.75 water. 95 C—5 min; 98 C—30 sec; 16 cycles of98 C—10 sec, 65 C—30 sec, 72 C—30 sec; 72 C—5 min; 4 C. Samples werecombined (equimolar) into 4-plex libraries based on the randomizationscheme and tested with the bioanalyzer for final size verification, andwith qPCR using phiX standards and adaptor-specific primers.

Samples were loaded onto flow cell lanes according to a randomized laneassignment with additional lanes reserved for internal assay controls.Sequencing was performed by the Next Generation Sequencing Core at theMayo Clinic Medical Genome Facility on the Illumina HiSeq 2000. Readswere unidirectional for 101 cycles. Each flow cell lane generated100-120 million reads, sufficient for a median coverage of 30-50 foldsequencing depth (read number per CpG) for aligned sequences. StandardIllumina pipeline software was used for base calling and sequence readgeneration in the fastq format. As previously (see, e.g., Sun, et al.,2012 Bioinformatics 28(16):2180-1), SAAP-RRBS, a streamlined analysisand annotation pipeline for reduced representation bisulfite sequencing,was used for sequence alignment and methylation extraction.

Two MSP-based validation studies were performed on expanded sample setsto confirm the accuracy and reproducibility of the observeddifferentially methylated candidates. The first, an internal validation(MSP) study, was performed on matched, blinded samples using biologicaland technical replicates of colorectal neoplasia, normal colon, andnormal leukocytes. This step was performed to ensure that the sites ofdifferential methylation identified by the RRBS data filtration, where %methylation was the unit of analysis, would be reflected in MSP, wherethe unit of analysis is the absolute genomic copy number of the targetsequence, corrected by the concentration of input DNA for each sample.The second, external validation experiment, utilized QuARTs technologyto test the top candidates in randomly allocated, matched, blinded,independent colorectal neoplasia and normal colon samples.

Primers for each marker were designed to target the bisulfite-modifiedmethylated sequences of each target gene (IDT, Coralville Iowa) and aregion without cytosine-phosphate-guanine sites in the β-actin gene, asa reference of bisulfite treatment and DNA input. The design was done byeither Methprimer software (University of California, San FranciscoCalif.) or by semi-manual methods. Assays were then tested and optimizedby running qPCR with SYBR Green (Life Technologies, Grand Island N.Y.)dyes on dilutions of universally methylated and unmethylated genomic DNAcontrols.

MSP reactions were performed on tissue-extracted DNA as previouslydescribed (see, e.g., Kisiel, et al., 2012 Cancer 118(10):2623-2631).Briefly, DNA was bisulfite treated using the EZ DNA Methylation Kit(Zymo Research, Orange, Calif.) and eluted in buffer. 1 μl ofbisulfite-treated DNA was used as a template for methylationquantification with a fluorescence-based real-time PCR, performed withSYBR Green master mix (Roche, Mannheim Germany). Reactions were run onRoche 480 LightCyclers (Indianapolis, Ind.), where bisulfite-treatedCpGenome Universal Methylated DNA (Millipore, Billerica, Mass.) was usedas a positive control, and serially diluted to create standard curvesfor all plates. Oligonucleotide sequences and annealing temperatures areavailable upon request.

The primary comparison of interest was the methylation differencebetween cases and colon controls at each mapped CpG. CpG islands arebiochemically defined by an observed to expected CpG ratio exceeding 0.6(31). However, for this model, tiled units of CpG analysis“differentially methylated region (DMR)” were created based on thedistance between CpG site locations for each chromosome. As the distancebetween any given CpG exceeded the previous or next location by morethan 100 bps, a new island identifier was created. Islands with only asingle CpG were excluded. The secondary outcome was the same comparisonbetween cases and leukocyte controls. Individual CpG sites wereconsidered for differential analysis only if the total depth of coverageper disease group was ≧200 reads (roughly equating to an average of 10reads per subject) and the variance of % methylation was greater thanzero (non-informative CpG sites with 0 variance were excluded). Thecriteria for read depth were based on the desired statistical power todetect a difference of 10% in the methylation rate between any twogroups in which the sample size of individuals for each group was 18.

Statistical significance was determined by logistic regression on the %methylation per DMR (using the actual counts) with the groups defined ascolorectal neoplasia, normal colon, and normal leukocytes. To accountfor varying read depths across individual subjects, an over-dispersedlogistic regression model was used, where dispersion parameter wasestimated using the Pearson Chi-square statistic of the residuals fromfitted model. To assess strand specific methylation, forward and reverseregions were analyzed separately. The DMRs were then ranked according totheir significance level and were considered as a viable marker regionif the methylation rate in the controls was ≦2.5% but ≧10% in cases.Each significant DMR was considered as a candidate marker.

For the internal validation study, the primary outcome was the areaunder the receiver operating characteristics curve (AUC) for eachmarker. This was calculated using logistic regression (JMP version9.0.1, SAS Institute, Cary N.C.) to model the strength of the mediancorrected copy number of each marker with colorectal neoplasia incomparison to normal colon and normal leukocytes. The markers with thehighest AUC values and widest ratio of median marker copy number betweencases and controls were selected for the external validation study. Theprimary outcome for the external validation experiment was the AUC foreach marker plotted against the signal strength of each marker, measuredby the log of the ratio of median corrected % methylation in casescompared to controls. With eighteen cases there is >80% power to detectan area under the curve of 0.85 or higher from the null hypothesis of0.5 at a two-sided significance level 0.05.

RRBS Marker Discovery

Matched, blinded, randomly allocated DNA extracts from 18 colorectalcancers, 18 advanced adenomas (>1 cm), 18 sessile serrated polyps, 18normal colon epithelial tissues, and 18 normal buffy coat derivedleukocyte controls were sequenced by RRBS. Median age was 65(interquartile range 60-70), and 51% were women. 4-5 million CpGs persample were generated from the sequencing data. After selecting only CpGsites where group coverage and variance criteria were met, anapproximate range of 2-3 million CpG sites were considered for furtheranalysis. SSA samples, which were derived from FFPE tissue blocks, had alower number of CpGs (200,000-1.2 million) due to lower inherentquality). 1068 (CRC), 1200 (advanced adenoma), and 268 (SSA) DMRs metsignificance criteria for differential methylation. These clustered into185, 244, and 109 candidate regions with sufficient methylationsignatures for MSP primer design. The length of DMRs ranged between 30to over 1000 bases. Methylation signatures contained 6 to 69 contiguousCpGs. 84% of the DMRs annotate to the 5′ regulatory (promoter) regionsof genes, most of which associate with larger CpG islands. In the caseof the CRC DMRs, approximately 15% have previous associations withcolorectal neoplasia. 50% have been reported in other types of cancer.Of the remaining 25%, approximately half segregate into cancer relevantpathways (transcription factors, signaling, cell cycle regulators,membrane transporters, etc.) A number of the annotated sites containmultiple DMRs.

Internal Validation

Based on the number of neighboring CpGs in each candidate genemethylation signature, primers were designed for the top 50 candidatesof the 185 CRC markers. Ranking was done by reference to logisticregression metrics and case/control copy number ratio. 35 of thesepassed internal performance QC and 15 were rejected. MSP was then usedto assay the 35 candidates in samples of DNA from additional matched,blinded, partially independent cohorts, including 36 CRC lesions, 36advanced adenomas, and 36 normal colonic epithelial samples. Inaddition, 31 DNA samples extracted from inflammatory bowel disease (IBD)patients (18 with CRC, 2 with high grade dysplasia, and 13 normalcontrols.) β-actin amplified in all samples. Of the 35 MSP assays, 18candidate markers had an AUC>0.88, case/control copy number ratios >50,and background methylation <1% (see Table 1A and 1B). These wereselected for inclusion in an independent external validation.

TABLE 1A Most Discriminate Markers in Independent Tissues by MSPincluding DMR Genomic Coordinates Back- ground Methyl- Median ationChromo- DMR Genomic Marker AUC S/N (%) some Coordinates FLI1 0.986 >10000 11 128563956-128564209 OPLAH 0.981 67 0.25 8 145106349-145106456 DTX10.974 >1000 0 12 113494586-113494957 MATK 0.972 64 0.63 193785828-3786371 SFMBT2 0.971 90 0.71 10 7452746-7452779 region 2 KCNK120.963 >1000 0 2 47797187-47797452 VAV3 0.954 135 0.27 1108507074-108507498 region 1 SFMBT2 0.952 >1000 0 10 7452885-7452956region 3 PPP2R5C 0.949 >1000 0.1 14 102247525-102247929 CHST20.947 >1000 0 3 142838645-142839023 region 2 PKIA 0.945 >1000 0.01 879428485-79428684 PDGFD 0.944 >1000 0 11 104034769-104034920 ELOVL20.935 70 0.79 6 11044395-11044834 CHST2 0.931 390 0.07 3142838025-142838494 region 1 SFMBT2 0.931 >1000 0 10 7452029-7452452region 1 QKI 0.921 50 0.61 6 163834534-163834925 VAV3 0.892 >1000 0 1108507609-108507674 region 2 SLC8A3 0.883 596 0.1 14 70655516-70655712

TABLE 1BMost Discriminate Markers in Independent Tissues by MSP includingForward MSP Primers and Reverse MSP Primers Marker Forward MSP PrimerReverse MSP Primer FLI1 GGGAGTGAGGGTAGGGCGTTC CTCGCAACCCCTTCGAATTAACCCG(SEQ ID NO: 1) (SEQ ID NO: 2) OPLAH TGCGTAGGTGATAGGGAGGGGTTACACAAAACACATCCTATTAACGCGAA (SEQ ID NO: 3) (SEQ ID NO: 4) DTX1GAGTCGCGGTTTCGTTTTC GACGCGACGACCGAAAAAC (SEQ ID NO: 5) (SEQ ID NO: 6)MATK TGCACACCCCGAGGCGGTCCCGG CGCCCCCAAAATAAAAAAACGAA (SEQ ID NO: 7)(SEQ ID NO: 8) SFMBT2 GCGTTTAGGTTGGTCGGAGA CCTAACCAACGCACTCAACC region 2(SEQ ID NO: 10) (SEQ ID NO: 11) KCNK12 CGTAGCGTGGCGTTTTAGCGCTCGAAAACCCCGACGAAACGAAAACG (SEQ ID NO: 12) (SEQ ID NO: 13) VAV3GCGTAAGGTCGAATATTTGAGTCGA AAAATACTACCCACCAACCACCGAA region 1(SEQ ID NO: 14) (SEQ ID NO: 15) SFMBT2 GTCGTCGTTCGAGAGGGTACGAACAAAAACGAACGAACGAA region 3 (SEQ ID NO: 16) (SEQ ID NO: 17) PPP2R5CTCGATTTTATTTTTGTTGTCGTTGTAGATTCGC GAAAAAACTAAAAAACGACAAAAAAACCCGACG(SEQ ID NO: 18) (SEQ ID NO: 19) CHST2 GGAACGAGTGATAGTCGGATAGTTCGTCCGCCCGAAAACGACCCCG region 2 (SEQ ID NO: 20) (SEQ ID NO: 21) PKIACGGGGATGATTTTATGTAGTCGGAGTTTCGC CCCGCCGAATACTCGATCAACTCG (SEQ ID NO: 22)(SEQ ID NO: 23) PDGFD GCGAATAAATAAACGTTAATTTGTTGTTTGTTTCCCGAACGCGTATAAATACCGCACTT (SEQ ID NO: 24) (SEQ ID NO: 25) ELOVL2CGGTTTTATTTATTATGATTCGTAGCGG CGACTACCCTAAACAACGCATCGC (SEQ ID NO: 26)(SEQ ID NO: 27) CHST2 CGAGTTCGGTAGTTGTACGTAGACGAAATACGAACGCGAAATCTAAAACT region 1 (SEQ ID NO: 28) (SEQ ID NO: 29)SFMBT2 GCGACGTAGTCGTCGTTGT CCAACGCGAAAAAAACGCG region 1 (SEQ ID NO: 30)(SEQ ID NO: 31) QKI GAGGCGGACGTCGCGGTAC CGCCACGACGCGAATCTTAACTACG(SEQ ID NO: 32) (SEQ ID NO: 33) VAV3 GGATCGAGGGAGTAGGAGTCGCCGAAACCGAACCTAACGCGACG region 2 (SEQ ID NO: 34) (SEQ ID NO: 35) SLC8A3AGTTTTTTCGCGCGTTTTTTTTGC GCCGAATCTCCGCCTTACACG (SEQ ID NO: 36)(SEQ ID NO: 37)

Logistic analyses were also run on the IBD case/control samples. Fromthe 35 tested markers, 3 markers (PDGFD, CHST2 7889, SFMBT2 896) werechosen for comparison with existing ColoGuard (Exact Sciences)methylation markers BMP3 and NDRG4 in an external stool basedvalidation.

External Validation

Matched, blinded, randomly allocated DNA from 40 CRC, 24 advancedadenomas, and 40 normal colon epithelial samples were assayed by QuARTsfor 18 top candidates. The median age of this subset was 60(interquartile range 52-67). Gender balance was 50:50. Same fordistal:proximal lesion percentages in cases. β-actin amplified in allsamples. All 18 markers demonstrated performance in line with theresults from the internal validation. In the CRC analysis, 9 markersexhibited superior performance in terms of both AUC characteristics andmethylation ratios between cases and controls. As shown in the tablebelow (Table 1C), these 9 showed excellent association with colorectalcancer.

TABLE 1C Most Discriminate Markers Showing Association with CRC Mean %ROC Std. Z Methylation − Marker AUC Error value Pr(>z) Lower.95 Upper.95Case/control vav3_877 0.8718 0.0354 10.5 0 0.8024 0.9412 5046 (VAV3region 2) chst2_7889 0.8462 0.0374 9.25 0 0.7728 0.9195 10127 (CHST2region 1) sfmbt2_896 0.9526 0.0251 18.05 0 0.9034 1.0017 139 (sfmbt2region 2) sfmbt2_895 0.9439 0.0266 16.72 0 0.8919 0.996 580 (sfmbt2region 1) pdgfd 0.8814 0.0351 10.85 0 0.8125 0.9503 1351 dtx1 0.96060.0222 20.77 0 0.9171 1.004 883 fli1 0.9744 0.0179 26.51 0 0.9393 1.00941131 sfmbt2_897 0.9311 0.0293 14.73 0 0.8737 0.9885 323 (sfmbt2 region3) chst2_7890 0.9231 0.0293 14.46 0 0.8657 0.9804 6970 (chst2 region 2)

For the IBD stool validation study, three markers were chosen—(PDGFD,CHST2 7889, SFMBT2 896), and run in comparison with BMP3 and NDRG4.

Methylated DNA markers were discovered and piloted to measure thedetection of IBD-associated CRN (IBD-CRN: low grade dysplasia [LGD],high grade dysplasia [HGD] and colorectal cancer [CRC]).

Markers were identified and tested in 3 discrete steps: discovery;biological validation; and clinical piloting. First a discoveryexperiment identified markers by reduced representation bisulfitesequencing (RRBS) on DNA extracted from archival frozen tissue samplesof sporadic CRC and adenomas. Second, candidate markers were validatedby methylation specific PCR (MSP) assay in DNA extracted from archivaltissues from IBD-CRC patients and IBD controls without CRN. Third,archival stools of independent IBD-CRN cases and IBD controls wereassayed by quantitative allele specific realtime target and signalamplification (QuARTS). Patients without surveillance biopsies or withprior solid organ transplant were excluded. Logistic regression measuredsensitivity and specificity. Clinical variable influence was tested byChi-square and Wilcoxon rank sum for categorical and continuous data,respectively.

18 sporadic CRC, 18 advanced adenomas and 18 normal colon samples weresequenced by RRBS; the top 20 candidates were tested by MSP inindependent samples including 18 IBD-CRC and 13 IBD-controls. Threemarkers (PDGFD, CHST2, SFMBT2) were selected for comparison to BMP3 andNDRG4; all were assayed by QuARTS in stool samples from 33 IBD-CRN cases(8 CRC, 8 HGD, 8 LGD≧1 cm, 10 LGD<1 cm) and 50 IBD controls. Fourcontrols were excluded for insufficient β-actin. Median IBD diseaseduration was 23 years (interquartile range [IQR] 9-35) in cases and 13(8-20) years in controls (p=0.0009). No other significant differenceswere seen when comparing age, sex, inflammation severity, IBD extent orco-morbid primary sclerosing cholangitis. PDGFD, CHST2, SFMBT2 levelswere modestly influenced by disease duration (p=0.04, 0.02, 0.04), butBMP3 and NDRG4 were not. Other variables were not significant. Detectionrates at 90% specificity are reported (Table 2A, 2B, and 2C).

For CRC (n=1) and HGD (n=2) samples that were negative, H&E blocks werereviewed. One HGD sample was re-classified as reactive change. DNA wasextracted from the remaining HGD and CRC tissues and assayed by QuARTSfor each marker above. These were strongly positive.

QuARTS assays were repeated on the corresponding stool samples withminimal change in % methylation; however, the raw copy numbers increasedfor each marker, such that BMP3, NDRG4, PDGFG, CHST27889 were able todetect 8/8 CRC and 6/7 HGD (14/15 CRC+HGD, 93% sensitivity) at aspecificity range of 89-93%.

TABLE 2A Detection of IBD-associated Colorectal Neoplasms by MethylatedStool DNA at 90% Specificity CRC + LGD ≧ LGD < Methylated CRC HGD HGD 1cm 1 cm marker (n = 8) (n = 16) (n = 8) (n = 8) (n = 10) BMP3 7 (88%) 13(81%) 6 (75%) 6 (75%) 6 (60%) NDRG4 7 (88%) 13 (81%) 6 (75%) 5 (63%) 4(40%) PDGFG 7 (88%) 13 (81%) 6 (75%) 4 (50%) 4 (40%) CHST2 7 (88%) 13(81%) 6 (75%) 5 (63%) 4 (40%) SFMBT2 7 (88%) 13 (81%) 6 (75%) 5 (63%) 3(30%)

TABLE 2B Detection of IBD-associated Colorectal Neoplasms by MethylatedStool DNA at 90% Specificity including DMR Genomic CoordinatesMethylated Chromo- DMR Genomic marker some Coordinates BMP3 481952348-81952402 NDRG4 16 58497395-58497451 PDGFG 11104034769-104034920 CHST2 3 142838025-142838494 SFMBT2 107452029-7452452

TABLE 2CDetection of IBD-associated Colorectal Neoplasms by Methylated Stool DNA at 90%Specificity including Forward MSP Primers, Probe Sequence, and Reverse MSP PrimersMethylated marker Forward Primer Probe Sequence Reverse Primer BMP3GTTTAATTTTCGGTTTCGTCGTC CGCCGAGGCGGTTTTTTGCG CGCTACGAAACACTCCGA(SEQ ID NO: 38) (SEQ ID NO: 39) (SEQ ID NO: 40) NDRG4CGGTTTTCGTTCGTTTTTTCG CCACGGACGGTTCGTTTATCG CCGCCTTCTACGCGACTA(SEQ ID NO: 41) (SEQ ID NO: 42) (SEQ ID NO: 43) PDGFGGCGAATAAATAAACGTTAATTTGTTGTTTGTTTC CCACGGACGCGCACTTCCTTACCGAACGCGTATAAATACCGCACTT (SEQ ID NO: 44) (SEQ ID NO: 45)(SEQ ID NO: 46) CHST2 CGAGTTCGGTAGTTGTACGTAGA CGCCGAGGTCGTCGATACCGCGAAATACGAACGCGAAATCTAAAACT (SEQ ID NO: 47) (SEQ ID NO: 48)(SEQ ID NO: 49) SFMBT2 GCGACGTAGTCGTCGTTGT CCACGGACGGAAAACGCGAAACCAACGCGAAAAAAACGCG (SEQ ID NO: 50) (SEQ ID NO: 51) (SEQ ID NO: 52)

Example 2

This example describes the identification of methylated DNA markers fordetection of colorectal cancer and pre-cancer.

Disclosed herein is a set of 185 DNA methylation markers for colorectalcancer (Tables 3A and 3B), 244 for large adenomas (≧1 cm) (Tables 4A and4B), and 111 for sessile serrated polyps (SSP) (Tables 5A and 5B)—allidentified from data generated by CpG island enrichment coupled withmassively parallel sequencing of a case—control tissue sample sets.Adenomas and SSPs are the critical precancerous lesions for CRC, andtheir detection in a screening application is important. Controlsincluded normal colonic epithelia and normal white blood cell derivedDNA. The technique utilized reduced representation bisulfite sequencing(RRBS). The tertiary and quaternary analyses are unique and integral tothe marker selection process. The tertiary step involves parsing thedata in terms of coverage cutoffs, excluding all non-informative sites,contrasting the % methylation between diagnostic subgroups usinglogistic regression, creating in-silico CpG “islands” based on definedgroupings of contiguous methylation sites, and Receiver OperatingCharacteristic analysis. The quaternary step filters the % methylationdata (both individual CpGs and the in-silico clusters) to select markerswhich maximize signal to noise ratios, minimize background methylation,account for tumor heterogeneity, and to emphasize ROC performance.Furthermore, this analytic approach insures identification of hotspotCpGs over a defined DNA length for easy development and optimal designof downstream marker assays—methylation specific PCR, small fragmentdeep sequencing, etc.

The CRC, adenoma, and control samples yielded approximately 2-3 millionhigh quality CpGs, which after analysis and filtering resulted inapproximately 1068 (CRC) and 1200 (adenoma) highly discriminateindividual sites. These clustered into 185 localized regions ofdifferential methylation for CRC and 244 for adenoma, some extending for30-40 bases and some greater than a kilobase. From a cursory literaturereview, less than 15% of the DMRs appear to have a previous colorectalcancer association. Nearly 50%, however, have some previous cancerassociation, but not specifically epigenetic in character. The rest haveeither very weak or no cancer associations, although many are involvedin functional pathways which may be relevant to tumorigenesis. 30 DMRs(CRC) and 42 (adenoma) had no annotation and no references anywhere inthe literature. These were named MAX followed by chromosomal locationand coordinates. All DMRs had AUCs of 0.85 or more (some demonstratedperfect discrimination of cases from controls with an AUC of 1.0). Inaddition to meeting the AUC threshold of 0.85, colon cancer and adenomamarkers that were identified had to exhibit >50-fold higher methylationdensity in tumor than in normal gastric or colonic mucosa and <1.0%methylation in normal colonic mucosa. Based on previous experience withpancreatic cancer marker discovery and validation, these markercharacteristics in tissue predict high discrimination in distant mediasuch as stool or blood.

The SSP samples were derived from FFPE blocks and were of lower quality.For these, only half had an adequate number of reads (>100,000). Assuch, the filtering stringencies were reduced slightly in comparison tothose used with the frozen samples. After sorting, there were 268discriminate sites which clustered into 111 localized regions.

Some of the disclosed markers are shared between pairwise case groups,and a lesser number between all three. Others are unique to a specificgroup. The majority are part of defined CpG islands (e.g. GC contentgreater than 55%, and an observed-to-expected CpG ratio of 65% or more),and where there is annotation (association with a known gene), thelocation is generally in the promoter region.

TABLE 3A Colorectal Cancer DMRs Chromo- Chromosome Gene some CoordinatesAnnotation 2 207308703-207308890 ADAM23 7 45613877-45613977 ADCY1 2224820148-24820373 ADORA2A 7 44143993-44144413 AEBP1 2100721643-100721967 AFF3 1 49242089-49242514 AGBL4 6 151561236-151561473AKAP12 7 134142981-134143723 AKR1B1 8 41754327-41754726 ANK1 1727940469-27940612 ANKRD13B 5 10565042-10565191 ANKRD33B 510564655-10564807 ANKRD33B 11 110582796-110583345 ARHGAP20 11110582170-110582657 ARHGAP20 11 110581912-110582039 ARHGAP20 12103351885-103352327 ASCL1 13 25946118-25946206 ATP8A2 8104152806-104153145 BAALC 9 96715112-96715603 BARX1 8 65493937-65494105BHLHE22 6 7727566-7728088 BMP6 6 105584685-105585220 BVES 1743339242-43339498 C17orf46 1 1475560-1475650 C1orf70 1 1476065-1476127C1orf70 10 16562866-16563332 C1QL3 10 16563667-16563892 C1QL3 1016562465-16562672 C1QL3 9 132382813-132382909 C9orf50 1870211543-70211719 CBLN2 3 128720801-128720885 CCDC48 3128719995-128720631 CCDC48 2 101033758-101034005 CHST10 12104850745-104851001 CHST11 3 142838025-142838494 CHST2 3142838645-142839023 CHST2 3 142839223-142839576 CHST2 5178016833-178017456 COL23A1 7 30721941-30722028 CRHR2 9124461296-124461420 DAB2IP 12 64062131-64062443 DPY19L2 12113494586-113494957 DTX1 10 64575060-64575283 EGR2 2 31456804-31457263EHD3 7 37487755-37488565 ELMO1 7 37487539-37487623 ELMO1 611044395-11044834 ELOVL2 6 80656845-80657306 ELOVL4 6152129389-152129636 ESR1 6 133562485-133562878 EYA4 15 48938056-48938252FBN1 11 128563956-128564209 FLI1 11 128562780-128563522 FLI1 6159590083-159590220 FNDC1 9 101471421-101471519 GABBR2 231360809-31360992 GALNT14 2 31360542-31360640 GALNT14 11134146132-134146380 GLB1L3 7 42276418-42277414 GLI3 12 52400569-52400726GRASP 12 52400919-52401166 GRASP 16 28074472-28074761 GSG1L 171959348-1959370 HIC1 7 50343838-50344453 IKZF1 2 182321830-182321983ITGA4 1 226925082-226925651 ITPKB 4 6201350-6201560 JAKMIP1 247797187-47797452 KCNK12 2 149633039-149633137 KIF5C 7149411729-149411847 KRBA1 19 8274584-8274671 LASS4 2 30455594-30455705LBH 5 38556357-38556743 LIFR 19 2290273-2290393 LINGO3 192290645-2290738 LINGO3 19 42905798-42906349 LIPE 7 140772542-140772873LOC100131199 2 100938402-100939005 LONRF2 7 127671918-127672318 LRRC4 1941119795-41119907 LTBP4 6 6546375-6546598 LY86-AS1 19 3785828-3786371MATK 10 22541502-22541671 MAX.chr10.22541502- 22541671 1022541884-22542001 MAX.chr10.22541884- 22542001 10 22765155-22765223MAX.chr10.22765155- 22765223 11 123301058-123301255 MAX.chr11.123301058-123301255 11 123301366-123301506 MAX.chr11.123301366- 123301506 11123301853-123301941 MAX.chr11.123301853- 123301941 11 57250528-57250611MAX.chr11.57250528- 57250611 12 8171360-8171769 MAX.chr12.8171360-8171769 14 100437680-100437767 MAX.chr14.100437680- 100437767 1922034447-22034696 MAX.chr19.22034447- 22034696 19 22034799-22034887MAX.chr19.22034799- 22034887 19 42444999-42445053 MAX.chr19.42444999-42445053 2 144694517-144695025 MAX.chr2.144694517- 144695025 2044936022-44936246 MAX.chr20.44936022- 44936246 3 13324501-13324623MAX.chr3.13324501- 13324623 3 13324760-13324864 MAX.chr3.13324760-13324864 3 44039952-44040054 MAX.chr3.44039952- 44040054 7142494755-142494915 MAX.chr7.142494755- 142494915 8 30769438-30769680MAX.chr8.30769438- 30769680 9 99983730-99984118 MAX.chr9.99983730-99984118 6 41606074-41606126 MDFI 3 150804938-150804971 MED12L 588185490-88185589 MEF2C 22 39853199-39853295 MGAT3 2 220416703-220417434MIR3132 6 132722283-132722484 MOXD1 8 72755813-72756349 MSC 1658497251-58497370 NDRG4 19 3361105-3361330 NFIC 17 47573986-47574084NGFR 7 108095348-108095805 NRCAM 8 32406662-32406901 NRG1 178925482-8925838 NTN1 15 53082447-53083044 ONECUT1 8 145106742-145106921OPLAH 8 145106349-145106456 OPLAH 5 76506245-76506578 PDE8B 11104034769-104034920 PDGFD 22 45405722-45405819 PHF21B 879428485-79428684 PKIA 1 150122783-150123157 PLEKHO1 1 38510915-38511213POU3F1 17 56833684-56833978 PPM1E 20 37434246-37434800 PPP1R16B 14102248062-102248216 PPP2R5C 14 102247525-102247929 PPP2R5C 1623847825-23848168 PRKCB 19 47778181-47778372 PRR24 6 163834534-163834925QKI 18 9708397-9709392 RAB31 20 4803201-4803703 RASSF2 2161263880-161264733 RBMS1 6 127440413-127441057 RSPO3 1726698693-26699117 SARM1 8 97505964-97506676 SDC2 17 75369224-75369327Septin9 17 75368800-75369056 Septin9 10 7452746-7452779 SFMBT2 107452885-7452956 SFMBT2 10 7452029-7452452 SFMBT2 10 7450242-7450831SFMBT2 10 7451097-7451185 SFMBT2 14 70655516-70655712 SLC8A3 5101632152-101632237 SLCO4C1 7 128829103-128829184 SMO 1165601167-65601514 SNX32 13 95363646-95363959 SOX21 12 24715703-24715776SOX5 12 24715012-24715416 SOX5 12 24716178-24716294 SOX5 1770114081-70114176 SOX9 7 75896637-75896925 SRRM3 6 166581771-166582044 T12 65218900-65218994 TBC1D30 12 65218335-65218778 TBC1D30 867874670-67875083 TCF24 18 53255390-53255565 TCF4 5 1294873-1295322 TERT21 32930226-32930576 TIAM1 21 32716063-32716545 TIAM1 274741941-74742264 TLX2 15 83776196-83776373 TM6SF1 2 135476019-135476390TMEM163 7 19156788-19156858 TWIST1 1 108507609-108507674 VAV3 1108507074-108507498 VAV3 5 82768837-82769031 VCAN 2 175547056-175547390WIPF1 8 10873760-10874271 XKR6 8 10872819-10873619 XKR6 1031609049-31609227 ZEB1 2 145274517-145274600 ZEB2 2 145274704-145275062ZEB2 19 58951402-58951530 ZNF132 19 54024023-54024436 ZNF331 1953661526-53662618 ZNF347 19 22018452-22018639 ZNF43 16 88496963-88497197ZNF469 19 37407197-37407365 ZNF568 19 12267378-12267677 ZNF625 1912203466-12203641 ZNF788 2 185463105-185463763 ZNF804A 1953970869-53971374 ZNF813

TABLE 3B Colorectal Cancer DMRs Ranked by Area Under the ROC Curve Areaunder Gene Chromo- Chromosome the ROC Annotation some Coordinate curveSFMBT2 10 7452885-7452956 1.0000 LIFR 5 38556357-38556743 0.9969 OPLAH 8145106742-145106921 0.9969 CRHR2 7 30721941-30722028 0.9966 AGBL4 149242089-49242514 0.9954 ZEB2 2 145274704-145275062 0.9938 ZNF788 1912203466-12203641 0.9936 SFMBT2 10 7452746-7452779 0.9926 ESR1 6152129389-152129636 0.9918 ANKRD33B 5 10565042-10565191 0.9907 CHST2 3142838645-142839023 0.9907 FNDC1 6 159590083-159590220 0.9902 ZNF469 1688496963-88497197 0.9899 AKR1B1 7 134142981-134143723 0.9892 OPLAH 8145106349-145106456 0.9886 MSC 8 72755813-72756349 0.9876 KCNK12 247797187-47797452 0.9861 MAX.chr10.22541884- 10 22541884-22542001 0.986122542001 ONECUT1 15 53082447-53083044 0.9861 RASSF2 20 4803201-48037030.9861 BHLHE22 8 65493937-65494105 0.9841 ARHGAP20 11110582170-110582657 0.9837 EYA4 6 133562485-133562878 0.9830 LINGO3 192290273-2290393 0.9830 MATK 19 3785828-3786371 0.9830 RSPO3 6127440413-127441057 0.9830 MGAT3 22 39853199-39853295 0.9828 GRASP 1252400919-52401166 0.9814 ZEB2 2 145274517-145274600 0.9806 GSG1L 1628074472-28074761 0.9804 ZNF625 19 12267378-12267677 0.9799 NDRG4 1658497251-58497370 0.9771 PPP2R5C 14 102247525-102247929 0.9771 FLI1 11128562780-128563522 0.9739 ZEB1 10 31609049-31609227 0.9739 C1QL3 1016562465-16562672 0.9737 C1orf70 1 1476065-1476127 0.9733 ANKRD13B 1727940469-27940612 0.9721 DAB2IP 9 124461296-124461420 0.9721 GALNT14 231360542-31360640 0.9721 ATP8A2 13 25946118-25946206 0.9716 CCDC48 3128720801-128720885 0.9707 LONRF2 2 100938402-100939005 0.9706 LRRC4 7127671918-127672318 0.9706 PDGFD 11 104034769-104034920 0.9706 SFMBT2 107452029-7452452 0.9706 SFMBT2 10 7450242-7450831 0.9706 CHST2 3142839223-142839576 0.9690 MAX.chr7.142494755- 7 142494755-1424949150.9690 142494915 MAX.chr11.123301058- 11 123301058-123301255 0.9673123301255 SOX9 17 70114081-70114176 0.9665 MAX.chr20.44936022- 2044936022-44936246 0.9659 44936246 TWIST1 7 19156788-19156858 0.9652ELMO1 7 37487539-37487623 0.9644 NFIC 19 3361105-3361330 0.9644 PLEKHO11 150122783-150123157 0.9644 POU3F1 1 38510915-38511213 0.9644 NGFR 1747573986-47574084 0.9633 LINGO3 19 2290645-2290738 0.9624 AEBP1 744143993-44144413 0.9613 PPP1R16B 20 37434246-37434800 0.9598 SFMBT2 107451097-7451185 0.9585 SMO 7 128829103-128829184 0.9583 FLI1 11128563956-128564209 0.9575 DTX1 12 113494586-113494957 0.9551 TIAM1 2132930226-32930576 0.9551 GABBR2 9 101471421-101471519 0.9542 PRKCB 1623847825-23848168 0.9539 RAB31 18 9708397-9709392 0.9536 VAV3 1108507074-108507498 0.9536 LASS4 19 8274584-8274671 0.9533 ANK1 841754327-41754726 0.9526 ANKRD33B 5 10564655-10564807 0.9520 SARM1 1726698693-26699117 0.9520 TM6SF1 15 83776196-83776373 0.9516 ZNF568 1937407197-37407365 0.9505 C1orf70 1 1475560-1475650 0.9497 ITGA4 2182321830-182321983 0.9495 GLB1L3 11 134146132-134146380 0.9493MAX.chr12.8171360- 12 8171360-8171769 0.9489 8171769MAX.chr14.100437680- 14 100437680-100437767 0.9481 100437767 ZNF132 1958951402-58951530 0.9479 BAALC 8 104152806-104153145 0.9474 CHST10 2101033758-101034005 0.9458 IKZF1 7 50343838-50344453 0.9443MAX.chr2.144694517- 2 144694517-144695025 0.9443 144695025 NRG1 832406662-32406901 0.9443 AFF3 2 100721643-100721967 0.9412 FBN1 1548938056-48938252 0.9412 C1QL3 10 16562866-16563332 0.9397 Septin9 1775368800-75369056 0.9396 MED12L 3 150804938-150804971 0.9387 MDFI 641606074-41606126 0.9381 MAX.chr11.123301366- 11 123301366-1233015060.9381 123301506 C9orf50 9 132382813-132382909 0.9375 ITPKB 1226925082-226925651 0.9365 TIAM1 21 32716063-32716545 0.9350 LTBP4 1941119795-41119907 0.9342 LOC100131199 7 140772542-140772873 0.9334 TCF248 67874670-67875083 0.9334 MAX.chr11.123301853- 11 123301853-1233019410.9321 123301941 SDC2 8 97505964-97506676 0.9319 TERT 5 1294873-12953220.9319 ELOVL2 6 11044395-11044834 0.9303 GALNT14 2 31360809-313609920.9298 Septin9 17 75369224-75369327 0.9289 GLI3 7 42276418-422774140.9288 SOX5 12 24715703-24715776 0.9286 BMP6 6 7727566-7728088 0.9272ELMO1 7 37487755-37488565 0.9257 HIC1 17 1959348-1959370 0.9246 VAV3 1108507609-108507674 0.9229 ELOVL4 6 80656845-80657306 0.9203 CCDC48 3128719995-128720631 0.9195 COL23A1 5 178016833-178017456 0.9195 PPM1E 1756833684-56833978 0.9195 PKIA 8 79428485-79428684 0.9186 ASCL1 12103351885-103352327 0.9180 ZNF347 19 53661526-53662618 0.9173MAX.chr19.22034447- 19 22034447-22034696 0.9164 22034696 NRCAM 7108095348-108095805 0.9164 C17orf46 17 43339242-43339498 0.9149 ARHGAP2011 110582796-110583345 0.9134 SOX5 12 24716178-24716294 0.9134 TLX2 274741941-74742264 0.9133 ZNF43 19 22018452-22018639 0.9131 BVES 6105584685-105585220 0.9118 CBLN2 18 70211543-70211719 0.9102MAX.chr19.42444999- 19 42444999-42445053 0.9080 42445053 BARX1 996715112-96715603 0.9071 GRASP 12 52400569-52400726 0.9071 PRR24 1947778181-47778372 0.9040 MAX.chr3.13324501- 3 13324501-13324623 0.903413324623 MAX.chr11.57250528- 11 57250528-57250611 0.9031 57250611 C1QL310 16563667-16563892 0.9025 MAX.chr3.13324760- 3 13324760-133248640.9003 13324864 KRBA1 7 149411729-149411847 0.9002 ADORA2A 2224820148-24820373 0.8957 TCF4 18 53255390-53255565 0.8955 TBC1D30 1265218900-65218994 0.8948 XKR6 8 10872819-10873619 0.8947 SLC8A3 1470655516-70655712 0.8922 NTN1 17 8925482-8925838 0.8916MAX.chr10.22765155- 10 22765155-22765223 0.8916 22765223MAX.chr10.22541502- 10 22541502-22541671 0.8884 22541671 MEF2C 588185490-88185589 0.8870 TBC1D30 12 65218335-65218778 0.8870MAX.chr9.99983730- 9 99983730-99984118 0.8854 99984118MAX.chr19.22034799- 19 22034799-22034887 0.8839 22034887 SOX21 1395363646-95363959 0.8839 ZNF804A 2 185463105-185463763 0.8839 SLCO4C1 5101632152-101632237 0.8805 ADAM23 2 207308703-207308890 0.8799 TMEM163 2135476019-135476390 0.8777 PDE8B 5 76506245-76506578 0.8769 EHD3 231456804-31457263 0.8762 MAX.chr8.30769438- 8 30769438-30769680 0.876230769680 QKI 6 163834534-163834925 0.8762 AKAP12 6 151561236-1515614730.8754 ADCY1 7 45613877-45613977 0.8731 LBH 2 30455594-30455705 0.8731SNX32 11 65601167-65601514 0.8731 PPP2R5C 14 102248062-102248216 0.8721MAX.chr3.44039952- 3 44039952-44040054 0.8715 44040054 RBMS1 2161263880-161264733 0.8715 ARHGAP20 11 110581912-110582039 0.8684 LIPE19 42905798-42906349 0.8684 SRRM3 7 75896637-75896925 0.8684 CHST2 3142838025-142838494 0.8669 XKR6 8 10873760-10874271 0.8669 WIPF1 2175547056-175547390 0.8653 VCAN 5 82768837-82769031 0.8628 KIF5C 2149633039-149633137 0.8612 MOXD1 6 132722283-132722484 0.8607 MIR3132 2220416703-220417434 0.8591 T 6 166581771-166582044 0.8591 DPY19L2 1264062131-64062443 0.8584 LY86-AS1 6 6546375-6546598 0.8560 ZNF331 1954024023-54024436 0.8545 PHF21B 22 45405722-45405819 0.8541 EGR2 1064575060-64575283 0.8529 ZNF813 19 53970869-53971374 0.8522 CHST11 12104850745-104851001 0.8514 SOX5 12 24715012-24715416 0.8514 JAKMIP1 46201350-6201560 0.8506

TABLE 4A Large Adenoma DMRs Chromo- Chromosome Gene some CoordinatesAnnotation 7 45613877-45613977 ADCY1 2 70994754-70995045 ADD2 2224820148-24820373 ADORA2A 2 100721643-100721967 AFF3 1 49242089-49242514AGBL4 6 151561236-151561473 AKAP12 6 151561598-151561873 AKAP12 7134142981-134143723 AKR1B1 8 41754327-41754726 ANK1 5 10564406-10564551ANKRD33B 5 10564655-10564807 ANKRD33B 5 10565042-10565191 ANKRD33B 11110582796-110583345 ARHGAP20 12 103351885-103352327 ASCL1 8104152806-104153145 BAALC 8 65494269-65494355 BHLHE22 6 7727566-7728088BMP6 6 105584685-105585220 BVES 12 21680721-21680828 C12orf39 1248577334-48577557 C12orf68 16 4588091-4588817 C16orf5 1 1475560-1475650C1orf70 1 1476065-1476127 C1orf70 10 16562866-16563332 C1QL3 1016563667-16563892 C1QL3 10 16562465-16562672 C1QL3 20 3388089-3388291C20orf194 6 74019826-74019955 C6orf147 9 132382813-132382909 C9orf50 744364925-44365359 CAMK2B 5 110559508-110560719 CAMK4 3 12838197-12838303CAND2 18 70211543-70211719 CBLN2 6 74405903-74406086 CD109 12133464655-133464819 CHFR 11 45686306-45686534 CHST1 2101033758-101034005 CHST10 12 104851372-104851465 CHST11 12104850745-104851001 CHST11 10 125852012-125852098 CHST15 10125852559-125852792 CHST15 10 125852905-125853007 CHST15 10125851544-125851700 CHST15 3 142838025-142838494 CHST2 3142838645-142839023 CHST2 3 142839223-142839576 CHST2 3139654045-139654299 CLSTN2 5 178016833-178017456 COL23A1 9124461296-124461420 DAB2IP 3 186079767-186080092 DGKG 165731412-65731782 DNAJC6 2 225906664-225906922 DOCK10 1264062131-64062443 DPY19L2 12 113494586-113494957 DTX1 2233352345-233352431 ECEL1 10 64575060-64575283 EGR2 2 31456804-31457263EHD3 7 37487755-37488565 ELMO1 6 11044395-11044834 ELOVL2 680656845-80657306 ELOVL4 6 152129389-152129636 ESR1 6133562229-133562380 EYA4 6 133562485-133562878 EYA4 7 23053043-23053438FAM126A 1 53098973-53099237 FAM159A 1 206137408-206137473 FAM72A 1120839339-120839381 FAM72B 1 120838272-120838775 FAM72B 1120836675-120836768 FAM72B 1 27960931-27961018 FGR 11128563956-128564209 FLI1 11 128562780-128563522 FLI1 1462584068-62584109 FLJ43390 13 28674199-28674862 FLT3 9101471421-101471519 GABBR2 2 31360809-31360992 GALNT14 1710102237-10102576 GAS7 19 19006296-19006511 GDF1 5 179780627-179781188GFPT2 5 137610023-137610333 GFRA3 11 134146132-134146380 GLB1L3 742276418-42277414 GLI3 1 54204505-54204712 GLIS1 12 52400919-52401166GRASP 10 88125930-88126495 GRID1 7 6570511-6570865 GRID2IP 1628074472-28074761 GSG1L 6 32632785-32632860 HLA-DQB1 1583621302-83621657 HOMER2 7 50343838-50344453 IKZF1 2 182321830-182321983ITGA4 21 46351838-46352381 ITGB2 1 226925082-226925651 ITPKB 46202051-6202410 JAKMIP1 4 6201350-6201560 JAKMIP1 2 47797187-47797452KCNK12 20 62103225-62103324 KCNQ2 6 73972941-73973104 KHDC1 2149633039-149633137 KIF5C 7 149411729-149411847 KRBA1 19 8274360-8274430LASS4 19 8274584-8274671 LASS4 19 2290273-2290393 LINGO3 1942905798-42906349 LIPE 11 8284746-8284871 LMO1 7 140773610-140773855LOC100131199 7 140772542-140772873 LOC100131199 2 100938402-100939005LONRF2 7 127671918-127672318 LRRC4 19 41119795-41119907 LTBP4 66546375-6546598 LY86-AS1 11 63828346-63828436 MACROD1 19 3785828-3786371MATK 1 244012766-244012875 MAX.chr1.244012766- 244012875 1244013190-244013393 MAX.chr1.244013190- 244013393 1 39269813-39270150MAX.chr1.39269813- 39270150 10 22541502-22541671 MAX.chr10.22541502-22541671 10 22541884-22542001 MAX.chr10.22541884- 22542001 1022765155-22765223 MAX.chr10.22765155- 22765223 11 120435350-120435981MAX.chr11.120435350- 120435981 11 123301058-123301255MAX.chr11.123301058- 123301255 11 123301366-123301506MAX.chr11.123301366- 123301506 11 123301853-123301941MAX.chr11.123301853- 123301941 11 44749119-44749205 MAX.chr11.44749119-44749205 11 8040551-8040677 MAX.chr11.8040551- 8040677 12133484966-133485857 MAX.chr12.133484966- 133485857 14100437680-100437767 MAX.chr14.100437680- 100437767 14105400087-105400182 MAX.chr14.105400087- 105400182 15 34806855-34807014MAX.chr15.34806855- 34807014 18 77558550-77558609 MAX.chr18.77558550-77558609 19 20959229-20959691 MAX.chr19.20959229- 20959691 1922034447-22034696 MAX.chr19.22034447- 22034696 19 22034799-22034887MAX.chr19.22034799- 22034887 2 144694517-144695025 MAX.chr2.144694517-144695025 21 47063135-47064177 MAX.chr21.47063135- 47064177 3115231555-115231576 MAX.chr3.115231555- 115231576 3 44039952-44040054MAX.chr3.44039952- 44040054 8 30769438-30769680 MAX.chr8.30769438-30769680 6 37664238-37664539 MDGA1 5 88185490-88185589 MEF2C 2239853199-39853295 MGAT3 17 74864552-74864821 MGAT5B 3154797723-154797909 MME 6 132722283-132722484 MOXD1 17 8533282-8534168MYH10 11 112832731-112832815 NCAM1 16 58497979-58498250 NDRG4 1747573986-47574084 NGFR 8 41503949-41504137 NKX6-3 5 142784971-142785160NR3C1 7 108095348-108095805 NRCAM 17 8925482-8925838 NTN1 1107683961-107684314 NTNG1 1 107683064-107683372 NTNG1 1107684447-107684545 NTNG1 3 13461109-13461191 NUP210 1179150971-79151076 ODZ4 15 53082447-53083044 ONECUT1 8145106742-145106921 OPLAH 8 145106349-145106456 OPLAH 3142682282-142682813 PAQR9 5 140855415-140856027 PCDHGA1 576506245-76506578 PDE8B 11 104034769-104034920 PDGFD 4 55099106-55099473PDGFRA 1 9711854-9711974 PIK3CD 8 79428485-79428684 PKIA 1150122783-150123157 PLEKHO1 1 38510915-38511213 POU3F1 1756833684-56833978 PPM1E 14 102248062-102248216 PPP2R5C 14102247525-102247929 PPP2R5C 5 122425730-122425886 PRDM6 2047444582-47444776 PREX1 16 23847825-23848168 PRKCB 16 23846951-23847056PRKCB 8 30890580-30890912 PURG 6 163834534-163834925 QKI 6163835376-163835472 QKI 20 4803969-4804077 RASSF2 20 4803201-4803703RASSF2 18 56936593-56936656 RAX 15 93631919-93632242 RGMA 977111900-77112005 RORB 6 127440413-127441057 RSPO3 17 26698693-26699117SARM1 8 97505964-97506676 SDC2 7 3339895-3340903 SDK1 1940005836-40005892 SELV 17 75368800-75369056 Septin9 22 26565137-26565417SEZ6L 10 7452746-7452779 SFMBT2 10 7452885-7452956 SFMBT2 107452029-7452452 SFMBT2 10 7450242-7450831 SFMBT2 10 7451097-7451185SFMBT2 6 118228394-118228979 SLC35F1 14 70655516-70655712 SLC8A3 1470655268-70655368 SLC8A3 11 65601167-65601514 SNX32 13 95363646-95363959SOX21 12 24715703-24715776 SOX5 12 24715012-24715416 SOX5 1224716178-24716294 SOX5 8 10587893-10588143 SOX7 7 75896637-75896925SRRM3 8 134583587-134583963 ST3GAL1 12 65218900-65218994 TBC1D30 1745810562-45810819 TBX21 8 67874670-67875083 TCF24 18 53255390-53255565TCF4 21 32931523-32931688 TIAM1 21 32930226-32930576 TIAM1 1583776196-83776373 TM6SF1 2 135476019-135476390 TMEM163 239893089-39893224 TMEM178 2 12857915-12858230 TRIB2 7 19156788-19156858TWIST1 1 213124472-213124778 VASH2 1 108507609-108507674 VAV3 1108507074-108507498 VAV3 5 82768837-82769031 VCAN 10 17271896-17271978VIM 10 17270955-17271052 VIM 13 27131683-27131757 WASF3 2175547056-175547390 WIPF1 1 228195339-228195413 WNT3A 810873760-10874271 XKR6 8 10872819-10873619 XKR6 10 31608798-31608892ZEB1 10 31608394-31608690 ZEB1 10 31609049-31609227 ZEB1 1958951402-58951530 ZNF132 4 332064-332199 ZNF141 17 16472295-16472694ZNF287 19 54024023-54024436 ZNF331 19 53661526-53662618 ZNF347 1922018746-22019004 ZNF43 16 88496963-88497197 ZNF469 19 37064200-37064435ZNF529 19 37960066-37960505 ZNF569 19 12267378-12267677 ZNF625 1920149796-20149923 ZNF682 2 185463105-185463763 ZNF804A

TABLE 4B Large Adenoma DMRs Ranked by Area Under the ROC Curve Areaunder Gene Chromo- Chromosome the ROC Annotation some Coordinate curveADD2 2 70994754-70995045 1.0000 AGBL4 1 49242089-49242514 1.0000 AKAP126 151561598-151561873 1.0000 ANKRD33B 5 10565042-10565191 1.0000 ASCL112 103351885-103352327 1.0000 C1orf70 1 1475560-1475650 1.0000 CHST11 12104851372-104851465 1.0000 CHST15 10 125851544-125851700 1.0000 DTX1 12113494586-113494957 1.0000 ECEL1 2 233352345-233352431 1.0000 EYA4 6133562485-133562878 1.0000 FLI1 11 128562780-128563522 1.0000 FLJ4339014 62584068-62584109 1.0000 FLT3 13 28674199-28674862 1.0000 GRASP 1252400919-52401166 1.0000 ITGA4 2 182321830-182321983 1.0000 KCNQ2 2062103225-62103324 1.0000 LOC100131199 7 140772542-140772873 1.0000LONRF2 2 100938402-100939005 1.0000 MGAT3 22 39853199-39853295 1.0000OPLAH 8 145106742-145106921 1.0000 OPLAH 8 145106349-145106456 1.0000PDE8B 5 76506245-76506578 1.0000 PDGFD 11 104034769-104034920 1.0000PKIA 8 79428485-79428684 1.0000 POU3F1 1 38510915-38511213 1.0000 QKI 6163834534-163834925 1.0000 RASSF2 20 4803201-4803703 1.0000 RSPO3 6127440413-127441057 1.0000 SDC2 8 97505964-97506676 1.0000 SFMBT2 107452746-7452779 1.0000 SFMBT2 10 7452029-7452452 1.0000 SFMBT2 107450242-7450831 1.0000 SOX5 12 24716178-24716294 1.0000 VAV3 1108507609-108507674 1.0000 VAV3 1 108507074-108507498 1.0000 ZNF132 1958951402-58951530 1.0000 ADCY1 7 45613877-45613977 0.9984 C1QL3 1016562465-16562672 0.9984 FLI1 11 128563956-128564209 0.9984 MYH10 178533282-8534168 0.9984 NTNG1 1 107683064-107683372 0.9984 ANKRD33B 510564655-10564807 0.9983 MAX.chr10.22541502- 10 22541502-22541671 0.998222541671 MAX.chr11.44749119- 11 44749119-44749205 0.9982 44749205GALNT14 2 31360809-31360992 0.9980 AKR1B1 7 134142981-134143723 0.9967CHST2 3 142839223-142839576 0.9967 EYA4 6 133562229-133562380 0.9967ZNF625 19 12267378-12267677 0.9967 LMO1 11 8284746-8284871 0.9965 ZNF46916 88496963-88497197 0.9964 ESR1 6 152129389-152129636 0.9951 KCNK12 247797187-47797452 0.9951 MAX.chr11.8040551- 11 8040551-8040677 0.99518040677 MOXD1 6 132722283-132722484 0.9951 PPP2R5C 14102247525-102247929 0.9951 PPP2R5C 14 102248062-102248216 0.9949 CHST1112 104850745-104851001 0.9948 LASS4 19 8274584-8274671 0.9945 GSG1L 1628074472-28074761 0.9935 MAX.chr11.120435350- 11 120435350-1204359810.9935 120435981 XKR6 8 10872819-10873619 0.9935 MAX.chr1.244012766- 1244012766-244012875 0.9933 244012875 DGKG 3 186079767-186080092 0.9931ITGB2 21 46351838-46352381 0.9931 MAX.chr19.22034447- 1922034447-22034696 0.9926 22034696 ZNF347 19 53661526-53662618 0.9921MAX.chr8.30769438- 8 30769438-30769680 0.9918 30769680 SOX5 1224715012-24715416 0.9918 CHST15 10 125852905-125853007 0.9913 ODZ4 1179150971-79151076 0.9913 SOX21 13 95363646-95363959 0.9908 SEZ6L 2226565137-26565417 0.9902 GAS7 17 10102237-10102576 0.9899MAX.chr11.123301853- 11 123301853-123301941 0.9889 123301941 ELMO1 737487755-37488565 0.9886 VIM 10 17270955-17271052 0.9886 WNT3A 1228195339-228195413 0.9886 SLC8A3 14 70655516-70655712 0.9879 PLEKHO1 1150122783-150123157 0.9869 SLC8A3 14 70655268-70655368 0.9869 ZNF682 1920149796-20149923 0.9869 ADORA2A 22 24820148-24820373 0.9857 ELOVL2 611044395-11044834 0.9853 GFRA3 5 137610023-137610333 0.9853 SOX5 1224715703-24715776 0.9847 EHD3 2 31456804-31457263 0.9837 TMEM163 2135476019-135476390 0.9837 MAX.chr14.105400087- 14 105400087-1054001820.9835 105400182 MACROD1 11 63828346-63828436 0.9833 ANKRD33B 510564406-10564551 0.9820 MATK 19 3785828-3786371 0.9820 NTNG1 1107683961-107684314 0.9820 ONECUT1 15 53082447-53083044 0.9820 WIPF1 2175547056-175547390 0.9820 GRID1 10 88125930-88126495 0.9804MAX.chr11.123301366- 11 123301366-123301506 0.9804 123301506 RASSF2 204803969-4804077 0.9804 TCF4 18 53255390-53255565 0.9804 TRIB2 212857915-12858230 0.9804 ZNF331 19 54024023-54024436 0.9804 SLC35F1 6118228394-118228979 0.9794 COL23A1 5 178016833-178017456 0.9788 FAM159A1 53098973-53099237 0.9788 GABBR2 9 101471421-101471519 0.9788 CHST2 3142838645-142839023 0.9775 MAX.chr19.22034799- 19 22034799-220348870.9775 22034887 CHST10 2 101033758-101034005 0.9771 GFPT2 5179780627-179781188 0.9771 IKZF1 7 50343838-50344453 0.9771 PRKCB 1623847825-23848168 0.9766 GRID2IP 7 6570511-6570865 0.9758 HOMER2 1583621302-83621657 0.9758 CHST1 11 45686306-45686534 0.9755MAX.chr18.77558550- 18 77558550-77558609 0.9753 77558609 LINGO3 192290273-2290393 0.9740 LASS4 19 8274360-8274430 0.9739 ZEB1 1031609049-31609227 0.9722 ZNF43 19 22018746-22019004 0.9722 C12orf39 1221680721-21680828 0.9706 MAX.chr10.22541884- 10 22541884-22542001 0.970622542001 MAX.chr11.123301058- 11 123301058-123301255 0.9706 123301255VIM 10 17271896-17271978 0.9699 AKAP12 6 151561236-151561473 0.9690C16orf5 16 4588091-4588817 0.9690 RORB 9 77111900-77112005 0.9690 NRCAM7 108095348-108095805 0.9689 ELOVL4 6 80656845-80657306 0.9683 CHST2 3142838025-142838494 0.9673 ITPKB 1 226925082-226925651 0.9673 PIK3CD 19711854-9711974 0.9673 SARM1 17 26698693-26699117 0.9673 GDF1 1919006296-19006511 0.9671 XKR6 8 10873760-10874271 0.9671 C9orf50 9132382813-132382909 0.9659 MAX.chr12.133484966- 12 133484966-1334858570.9657 133485857 PURG 8 30890580-30890912 0.9643 AFF3 2100721643-100721967 0.9641 PDGFRA 4 55099106-55099473 0.9641MAX.chr3.44039952- 3 44039952-44040054 0.9637 44040054 TWIST1 719156788-19156858 0.9632 MEF2C 5 88185490-88185589 0.9608 VCAN 582768837-82769031 0.9602 NCAM1 11 112832731-112832815 0.9600 CAMK4 5110559508-110560719 0.9592 TBC1D30 12 65218900-65218994 0.9587 BMP6 67727566-7728088 0.9585 BAALC 8 104152806-104153145 0.9575 GLB1L3 11134146132-134146380 0.9575 KRBA1 7 149411729-149411847 0.9569 TCF24 867874670-67875083 0.9550 NTN1 17 8925482-8925838 0.9542 CAMK2B 744364925-44365359 0.9516 MAX.chr2.144694517- 2 144694517-1446950250.9510 144695025 SDK1 7 3339895-3340903 0.9510 SRRM3 7 75896637-758969250.9498 CLSTN2 3 139654045-139654299 0.9493 SELV 19 40005836-400058920.9487 LY86-AS1 6 6546375-6546598 0.9477 PPM1E 17 56833684-568339780.9477 TM6SF1 15 83776196-83776373 0.9462 MAX.chr1.244013190- 1244013190-244013393 0.9461 244013393 MAX.chr1.39269813- 139269813-39270150 0.9461 39270150 MAX.chr14.100437680- 14100437680-100437767 0.9446 100437767 EGR2 10 64575060-64575283 0.9444SOX7 8 10587893-10588143 0.9428 LRRC4 7 127671918-127672318 0.9395 RGMA15 93631919-93632242 0.9395 ZNF804A 2 185463105-185463763 0.9395 C1QL310 16562866-16563332 0.9373 SFMBT2 10 7451097-7451185 0.9366 CHFR 12133464655-133464819 0.9360 JAKMIP1 4 6201350-6201560 0.9360 ANK1 841754327-41754726 0.9346 FAM126A 7 23053043-23053438 0.9346 SFMBT2 107452885-7452956 0.9338 MME 3 154797723-154797909 0.9329 BHLHE22 865494269-65494355 0.9323 DPY19L2 12 64062131-64062443 0.9314 VASH2 1213124472-213124778 0.9302 PREX1 20 47444582-47444776 0.9286 ARHGAP20 11110582796-110583345 0.9248 MAX.chr10.22765155- 10 22765155-227652230.9242 22765223 ZNF141 4 332064-332199 0.9221 DNAJC6 1 65731412-657317820.9216 PCDHGA1 5 140855415-140856027 0.9216 QKI 6 163835376-1638354720.9213 MAX.chr3.115231555- 3 115231555-115231576 0.9199 115231576 GLIS11 54204505-54204712 0.9178 ZEB1 10 31608394-31608690 0.9150 BVES 6105584685-105585220 0.9134 LOC100131199 7 140773610-140773855 0.9134PAQR9 3 142682282-142682813 0.9134 CD109 6 74405903-74406086 0.9126 RAX18 56936593-56936656 0.9091 C12orf68 12 48577334-48577557 0.9069 SNX3211 65601167-65601514 0.9069 HLA-DQB1 6 32632785-32632860 0.9058 PRKCB 1623846951-23847056 0.9053 GLI3 7 42276418-42277414 0.9036 Septin9 1775368800-75369056 0.9031 FAM72A 1 206137408-206137473 0.9016 NDRG4 1658497979-58498250 0.9003 FAM72B 1 120838272-120838775 0.8995 KIF5C 2149633039-149633137 0.8990 JAKMIP1 4 6202051-6202410 0.8989 CHST15 10125852559-125852792 0.8989 MDGA1 6 37664238-37664539 0.8987 NGFR 1747573986-47574084 0.8981 ZEB1 10 31608798-31608892 0.8979 ZNF529 1937064200-37064435 0.8979 ZNF287 17 16472295-16472694 0.8962 C1orf70 11476065-1476127 0.8962 C20orf194 20 3388089-3388291 0.8932 TIAM1 2132930226-32930576 0.8910 NR3C1 5 142784971-142785160 0.8895 CBLN2 1870211543-70211719 0.8873 NKX6-3 8 41503949-41504137 0.8858 TMEM178 239893089-39893224 0.8856 KHDC1 6 73972941-73973104 0.8845 PRDM6 5122425730-122425886 0.8824 ST3GAL1 8 134583587-134583963 0.8824 FAM72B 1120839339-120839381 0.8815 DAB2IP 9 124461296-124461420 0.8787 CHST15 10125852012-125852098 0.8780 C6orf147 6 74019826-74019955 0.8775MAX.chr21.47063135- 21 47063135-47064177 0.8775 47064177 TIAM1 2132931523-32931688 0.8772 C1QL3 10 16563667-16563892 0.8758 NUP210 313461109-13461191 0.8755 FAM72B 1 120836675-120836768 0.8736MAX.chr15.34806855- 15 34806855-34807014 0.8722 34807014 CAND2 312838197-12838303 0.8719 TBX21 17 45810562-45810819 0.8702 MGAT5B 1774864552-74864821 0.8685 ZNF569 19 37960066-37960505 0.8676 NTNG1 1107684447-107684545 0.8672 WASF3 13 27131683-27131757 0.8647 LIPE 1942905798-42906349 0.8644 DOCK10 2 225906664-225906922 0.8578 LTBP4 1941119795-41119907 0.8546 MAX.chr19.20959229- 19 20959229-20959691 0.852120959691 FGR 1 27960931-27961018 0.8513

TABLE 5A Sessile Serrated Polyps (SSP) DMR Chromo- Chromosome Gene someCoordinates Annotation 5 10564655-10564710 ANKRD33B 12103351885-103351983 ASCL1 1 203598574-203598800 ATP2B4 691005003-91005091 BACH2 6 7727026-7727129 BMP6 6 105584890-105584983BVES 10 21784521-21784567 C10orf114 1 226737152-226737231 C1orf95 5110559571-110559638 CAMK4 2 56411545-56411640 CCDC85A 1158150837-158150885 CD1D 1 158151102-158151205 CD1D 10 90967004-90967028CH25H 2 101033768-101033858 CHST10 12 104850745-104850879 CHST11 3142838194-142838411 CHST2 9 34590231-34590344 CNTFR 12 49484149-49484231DHH 15 30484732-30484813 DKFZP434L187 1 65731412-65731530 DNAJC6 2225906664-225906763 DOCK10 2 225907515-225907632 DOCK10 273520956-73520964 EGR4 6 80656889-80656974 ELOVL4 6 80657208-80657306ELOVL4 5 111754713-111754810 EPB41L4A 3 96532270-96532344 EPHA6 723053937-23054066 FAM126A 11 125365196-125365327 FEZ1 1322243643-22243727 FGF9 7 90894876-90894960 FZD1 17 42907793-42907827GJC1 3 179169408-179169505 GNB4 1 101005577-101005661 GPR88 153068071-53068182 GPX7 7 6570755-6570845 GRID2IP 16 10275378-10275472GRIN2A 17 14205388-14205498 HS3ST3B1 7 23509037-23509225 IGF2BP3 639281409-39281488 KCNK17 15 79724426-79724525 KIAA1024 2208031024-208031104 KLF7 2 208031731-208031826 KLF7 2 30454421-30454492LBH 2 30454871-30454977 LBH 2 74726179-74726265 LBX2 5 87970308-87970374LOC645323 5 87970772-87970894 LOC645323 2 170220089-170220148 LRP2 1240618617-40618655 LRRK2 1 25944147-25944152 MAN1C1 11123301366-123301387 MAX.chr11.123301366- 123301387 17 45867397-45867662MAX.chr17.45867397- 45867662 19 55963254-55963329 MAX.chr19.55963254-55963329 2 127783352-127783403 MAX.chr2.127783352- 127783403 296192422-96192521 MAX.chr2.96192422- 96192521 20 1783778-1783841MAX.chr20.1783778- 1783841 22 42310340-42310438 MAX.chr22.42310340-42310438 3 43935668-43935753 MAX.chr3.43935668- 43935753 4186049639-186049660 MAX.chr4.186049639- 186049660 6 114664537-114664631MAX.chr6.114664537- 114664631 7 127807622-127807693 MAX.chr7.127807622-127807693 7 149745500-149745592 MAX.chr7.149745500- 149745592 9114074-114160 MAX.chr9.114074- 114160 9 114354-114435 MAX.chr9.114354-114435 9 99983903-99984118 MAX.chr9.99983903- 99984118 637664654-37664664 MDGA1 15 66546092-66546108 MEGF11 15 82339716-82339790MEX3B 11 30607877-30607973 MPPED2 4 113437673-113437953 NEUROG2 1153651840-153651933 NPR1 5 142785023-142785050 NR3C1 8 32406662-32406739NRG1 1 40137384-40137471 NT5C1A 1 107684212-107684314 NTNG1 1107683064-107683130 NTNG1 5 140855796-140855883 PCDHGA1 19711931-9711974 PIK3CD 2 198669944-198670044 PLCL1 1 150122951-150122989PLEKHO1 14 102247811-102247881 PPP2R5C 9 33677215-33677313 PTENP1 189708795-9708891 RAB31 18 9708515-9708598 RAB31 1 167599730-167599772RCSD1 1 44872395-44872487 RNF220 9 94712910-94712961 ROR2 977111911-77112005 RORB 17 1928103-1928210 RTN4RL1 1 101702045-101702063S1PR1 1 860904-860978 SAMD11 22 42949849-42949919 SERHL2 107450571-7450659 SFMBT2 1 220101492-220101587 SLC30A10 6118228394-118228493 SLC35F1 12 24715012-24715060 SOX5 1224715174-24715255 SOX5 10 73847865-73847982 SPOCK2 18 52989026-52989191TCF4 13 43148769-43148861 TNFSF11 9 135285696-135285788 TTF1 6149069140-149069222 UST 3 55521770-55521861 WNT5A 10 31608625-31608690ZEB1 19 58666209-58666308 ZNF329 19 20149832-20149923 ZNF682 1953073640-53073729 ZNF701 7 6655558-6655640 ZNF853

TABLE 5B Sessile Serrated Polyps (SSP) DMR Ranked by Area Under the ROCCurve Area under Gene Chromo- Chromosome the ROC Annotation someCoordinate curve CAMK4 5 110559571-110559638 1.0000 FGF9 1322243643-22243727 1.0000 GJC1 17 42907793-42907827 1.0000 GPX7 153068071-53068182 1.0000 GRIN2A 16 10275378-10275472 1.0000 IGF2BP3 723509037-23509225 1.0000 MAX.chr19.55963254- 19 55963254-55963329 1.000055963329 MAX.chr2.127783352- 2 127783352-127783403 1.0000 127783403MAX.chr4.186049639- 4 186049639-186049660 1.0000 186049660 NRG1 832406662-32406739 1.0000 NTNG1 1 107684212-107684314 1.0000 PIK3CD 19711931-9711974 1.0000 PTENP1 9 33677215-33677313 1.0000 RAB31 189708795-9708891 1.0000 RNF220 1 44872395-44872487 1.0000 SLC30A10 1220101492-220101587 1.0000 ZNF853 7 6655558-6655640 1.0000 LBH 230454871-30454977 0.9967 DOCK10 2 225906664-225906763 0.9958 MEX3B 1582339716-82339790 0.9951 PCDHGA1 5 140855796-140855883 0.9926 FZD1 790894876-90894960 0.9916 GNB4 3 179169408-179169505 0.9916 MAN1C1 125944147-25944152 0.9916 ZNF701 19 53073640-53073729 0.9916 DKFZP434L18715 30484732-30484813 0.9902 RTN4RL1 17 1928103-1928210 0.9902MAX.chr20.1783778- 20 1783778-1783841 0.9890 1783841 SPOCK2 1073847865-73847982 0.9853 MAX.chr7.149745500- 7 149745500-1497455920.9804 149745592 HS3ST3B1 17 14205388-14205498 0.9748 LRP2 2170220089-170220148 0.9748 MAX.chr9.114354- 9 114354-114435 0.9748114435 ELOVL4 6 80656889-80656974 0.9706 ELOVL4 6 80657208-806573060.9706 MPPED2 11 30607877-30607973 0.9706 MAX.chr17.45867397- 1745867397-45867662 0.9664 45867662 CD1D 1 158150837-158150885 0.9618ATP2B4 1 203598574-203598800 0.9559 C10orf114 10 21784521-217845670.9496 KCNK17 6 39281409-39281488 0.9485 FEZ1 11 125365196-1253653270.9429 PLCL1 2 198669944-198670044 0.9363 CD1D 1 158151102-1581512050.9314 NT5C1A 1 40137384-40137471 0.9286 MAX.chr9.99983903- 999983903-99984118 0.9191 99984118 GPR88 1 101005577-101005661 0.9069RAB31 18 9708515-9708598 0.9069 NR3C1 5 142785023-142785050 0.9048 S1PR11 101702045-101702063 0.9044 SOX5 12 24715012-24715060 0.9044 EPB41L4A 5111754713-111754810 0.9034 LOC645323 5 87970772-87970894 0.9034 CHST1112 104850745-104850879 0.8971 ROR2 9 94712910-94712961 0.8946MAX.chr22.42310340- 22 42310340-42310438 0.8918 42310438 RORB 977111911-77112005 0.8905 ZEB1 10 31608625-31608690 0.8897 NEUROG2 4113437673-113437953 0.8856 TCF4 18 52989026-52989191 0.8807MAX.chr3.43935668- 3 43935668-43935753 0.8750 43935753 KLF7 2208031731-208031826 0.8739 ZNF682 19 20149832-20149923 0.8739 DOCK10 2225907515-225907632 0.8732 MDGA1 6 37664654-37664664 0.8725 LBH 230454421-30454492 0.8718 WNT5A 3 55521770-55521861 0.8718 BVES 6105584890-105584983 0.8706 SAMD11 1 860904-860978 0.8706 MEGF11 1566546092-66546108 0.8701 LRRK2 12 40618617-40618655 0.8697 BACH2 691005003-91005091 0.8687 CHST10 2 101033768-101033858 0.8676 CHST2 3142838194-142838411 0.8676 MAX.chr9.114074- 9 114074-114160 0.8664114160 EGR4 2 73520956-73520964 0.8627 NTNG1 1 107683064-1076831300.8613 TTF1 9 135285696-135285788 0.8613 SOX5 12 24715174-247152550.8611 ASCL1 12 103351885-103351983 0.8603 KLF7 2 208031024-2080311040.8600 CNTFR 9 34590231-34590344 0.8592 MAX.chr6.114664537- 6114664537-114664631 0.8592 114664631 SFMBT2 10 7450571-7450659 0.8585TNFSF11 13 43148769-43148861 0.8571 DNAJC6 1 65731412-65731530 0.8550GRID2IP 7 6570755-6570845 0.8550 BMP6 6 7727026-7727129 0.8474MAX.chr11.123301366- 11 123301366-123301387 0.8471 123301387 PPP2R5C 14102247811-102247881 0.8466 SERHL2 22 42949849-42949919 0.8464 RCSD1 1167599730-167599772 0.8456 MAX.chr2.96192422- 2 96192422-96192521 0.843196192521 ANKRD33B 5 10564655-10564710 0.8407 NPR1 1 153651840-1536519330.8384 EPHA6 3 96532270-96532344 0.8267 FAM126A 7 23053937-230540660.8262 CH25H 10 90967004-90967028 0.8235 KIAA1024 15 79724426-797245250.8235 LOC645323 5 87970308-87970374 0.8235 ZNF329 19 58666209-586663080.8224 UST 6 149069140-149069222 0.8199 CCDC85A 2 56411545-564116400.8193 PLEKHO1 1 150122951-150122989 0.8176 SLC35F1 6118228394-118228493 0.8082 LBX2 2 74726179-74726265 0.8059 DHH 1249484149-49484231 0.8046 MAX.chr7.127807622- 7 127807622-1278076930.8007 127807693 C1orf95 1 226737152-226737231 0.8000

Example 3

This example demonstrates NDRG4, BMP3, OPLAH, FLI1, PDGFD, CHST_7889,SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890, VAV3, and DTX1 aseffective markers for detecting colorectal cancer within stool samples.

Forward and reverse primer and probe sequences for NDRG4, BMP3, OPLAH,FLI1, PDGFD, CHST_7889, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890,VAV3, and DTX1 are provided in Table 6A. Table 6B provides informationregarding the methylated marker, chromosome and DMR genomic coordinatesprovided in Table 6A.

Capture probes for each marker were designed to have a meltingtemperature of 75-80° C. and lengths between 25-35 bases (see, Table6C). Additionally, the capture probe hybridizing region was selected tobe within the post-bisulfite QuARTS footprint. Table 6C provides themethylation marker and respective capture probe sequences.

TABLE 6AForward Primer, Probe, Reverse Primer Sequences for Markers Utilized in Example 3Methylation Marker Forward Primer Probe Sequence Reverse Primer VAV3TCGGAGTCGAGTTTAGCGC CCACGGACG-CGGCGTTCGCGA/3C6/ CGAAATCGAAAAAACAAAAACCGC(SEQ ID NO: 54) (SEQ ID NO: 55) (SEQ ID NO: 56) CHST2_7889CGAGTTCGGTAGTTGTACG CGCCGAGG-TCGTCGATACCG/3C6/ CGAAATACGAACGCGAAATCTAAATAGA (SEQ ID NO: 58) ACT (SEQ ID NO: 57) (SEQ ID NO: 59) SFMBT2_897GTcGTcGTTcGAGAGGGTA CCACGGACG-ATCGGTTTCGTT/3C6/ CGAACAAAAACGAACGAACGAA(SEQ ID NO: 60) (SEQ ID NO: 61) (SEQ ID NO: 62) SFMBT2_896GCGTTTAGGTTGGTCGGAG CGCCGAGG-CTACGAACCGAA/3C6/ CCTAACCAACGCACTCAACCA (Version 1) (Version 1) (Version 1) (SEQ ID NO: 63) (SEQ ID NO: 64)(SEQ ID NO: 65) GCGTTTAGGTTGGTCGGAG CGCCGAGGCCGAAAAACTAC/3C6/ACGCACTCAACCTACGAAC (Version 2) (Version 2) (Version 2) (SEQ ID NO: 90)(SEQ ID NO: 91) (SEQ ID NO: 92) SFMBT2_895 TTAGCGAcGTAGTcGTcGTCCACGGACG-CGAAAACGCGAA/3C6/ CCCAACGCGAAAAAAACGC TG (Version 1)(Version 1) (Version 1) (SEQ ID NO: 66) (SEQ ID NO: 67) (SEQ ID NO: 68)GCGACGTAGTCGTCGTTGT CCACGGACGGAAAACGCGAAA/3C6/ CCAACGCGAAAAAAACGCG(Version 2) (Version 2) (Version 2) (SEQ ID NO: 93) (SEQ ID NO: 94)(SEQ ID NO: 95) CHST2_7890 GTATAGCGCGATTTCGTAGCGCCGAGG-CGAACATCCTCC/3C6/ AATTACCTACGCTATCCGCCC cG (SEQ ID NO: 70)(SEQ ID NO: 71) (SEQ ID NO: 69) OPLAH cGTcGcGTTTTTcGGTTATCCACGGACG-GCACCGTAAAAC/3C6/ CGCGAAAACTAAAAAACCGCG ACG (SEQ ID NO: 73)(SEQ ID NO: 74) (SEQ ID NO: 72) PDGFD AAACGTTAATTTGTTGTTTACTTTCCGAACGCGTATAAATACC GCGAATAAATAAACGTTAATTTGT GTTTCGTT (Version 1)(Version 1) TGTTTGTTTCG (SEQ ID NO: 75) (SEQ ID NO: 76) (Version 1)GCGAATAAATAAACGTTAA CCACGGACGCGCACTTCCTTA/3C6/ (SEQ ID NO: 77)TTTGTTGTTTGTTTCG (Version 2) ACTTTCCGAACGCGTATAAATACC (Version 2)(SEQ ID NO: 97) (Version 2) (SEQ ID NO: 96) (SEQ ID NO: 98) FLI1GTTGcGAGGTTAGGTTGTA CGCCGAGG-CGTCCATTTAAC/3C6/ CGCCGCTTACCTTAATAATCCCATCG (SEQ ID NO: 79) (SEQ ID NO: 80) (SEQ ID NO: 78) DTX1GAGTCGCGGTTTCGTTTTC CGCCGAGG-CGCGTTCGTTTT/3C6/ GACGCGACGACCGAAAAAC(SEQ ID NO: 81) (SEQ ID NO: 82) (SEQ ID NO: 83) NDRG4CGGTTTTCGTTCGTTTTTT CCACGGACGGTTCGTTTATCG/3C6/ CCGCCTTCTACGCGACTA CG(SEQ ID NO: 85) (SEQ ID NO: 86) (SEQ ID NO: 84) BMP3 GTTTAATTTTCGGTTTCGTCGCCGAGGCGGTTTTTTGCG/3C6/ CGCTACGAAACACTCCGA CGTC (SEQ ID NO: 88)(SEQ ID NO: 89) (SEQ ID NO: 87)

TABLE 6B Methylated marker, chromosome and DMR genomic coordinates.Methylated Chromo- DMR Genomic marker some Coordinates BMP3 481031173-81031262 NDRG4 16 58463478-58463588 VAV3 1 107964966-107965057CHST2_7889 3 143119424-143119583 SFMBT2_897 10 7410903-7411014SFMBT2_896 10 7410764-7410837 SFMBT2_895 10 7410331-7410490 CHST2_7890 3143119999-143120158 OPLAH 8 144051847-144052006 PDGFD 11104164082-104164186 FLI1 11 128694158-128694317 DTX1 12113056762-113056895

TABLE 6C Methylation marker and respective capture probe sequences.Methylation Marker Capture Probe Sequence VAV3/5AmMC6/GATCGAGGGAGCAGGAGCCGCGGCTGAC GGGTCGCG (SEQ ID NO: 99) CHST2_7889/5AmMC6/CGGTGCCGAGAGCTGCCAGAGAGTTGGA TTCTGCG (SEQ ID NO: 100) SFMBT2_897/5AmMC6/GCGAGCGGGCAAGGGCGGGCGAGC (SEQ ID NO: 101) SFMBT2_896/5AmMC6/ACCTGCGGGCCGAAGGGCTGCTCTCCGG (SEQ ID NO: 102) SFMBT2_895/5AmMC6/AGGAGACGCGGGAGCGCGGGGTAGGTAG C (SEQ ID NO: 103) CHST2_7890/5AmMC6/GGCATCCTCCCGGTGATGGAAGCAGCCG CCGCCG (SEQ ID NO: 104) OPLAH/5AmMC6/GGAAGGCGCGGCGCTCGGTCAGCACTGA CAGCAG (SEQ ID NO: 105) PDGFD/5AmMC6/TCGCCGAGCTCTCCCCAAACTTCCTGCA TGCTGAACTTT (SEQ ID NO: 106) FLI1/5AmMC6/CCGTCCATTTGGCCAAGTCTGCAGCCGA GCC (SEQ ID NO: 107) DTX1/5AmMC6/CTGCGTCCGTCCGTCGGCCGGGCAGTCT GTCCA (SEQ ID NO: 108) NDRG4/5AmMC6/TCCCTCGCGCGTGGCTTCCGCCTTCTGC GCGGCTGGGGTGCCCGGTGG(SEQ ID NO: 109) BMP3 /5AmMC6/GCGGGACACTCCGAAGGCGCAAGGAG(SEQ ID NO: 110)

Each capture probe was synthesized with a 5′-NH2 modification to allowcoupling to magnetic particles that are —COOH modified through standardcarbodiimide coupling chemistry. Also, a complementary oligonucleotideto the capture probe was synthesized to contain a 5′-Cy3 label. Thiscomplementary probe was used to confirm capture probe coupling tomagnetic particles.

To test the capture efficiency of each probe as well as assess markerperformance, two stool pools of normal and cancer patients were made.The cancer stool pool came from 6 patients (3 are CRC, 1 is an AA and 2unknowns). Similarly, the normal stool came from 6 non-CRC normalpatients. The stool was prepared by mixing the supernatant afterhomogenate centrifugation. Pooled supernatant was then aliquoted intosingle capture samples containing 14 mL supernatants.

Capture probes were designed to have a melting temperature of 75-80° C.and lengths between 25-35 bases. Additionally, the capture probehybridizing region was selected to be within the post-bisulfite QuARTSfootprint.

To perform capture, capture beads (magnetic particles with covalentlylinked capture probes) for two markers plus ACTB capture beads werepooled to form a triplex capture bead pool.

Capture was performed on triplicates 14 mL of positive and normal stoolsupernatants (exception was VAV3 and DTX1 were performed in duplicatessince pool was running low).

After completion of capture, stool DNA was eluted from capture beadswith 0.1 N NaOH at 42° C. for 20 minutes followed by bisulfiteconversion at 56° C. for 1 hour using ammonium bisulfite. Stool DNA wasthen desulphonated and purified using silica coated magnetic beads andeluted in 70 uL of 10 mM Tris-HCl, pH 8, 0.1 mM EDTA. 10 uL of eluentwas then tested and quantified in QuARTS assays.

To be able to quantify samples, pUC57 plasmids with DNA insertscorresponding to the QuARTS footprints were used. The DNA inserts wereflanked with EcoRI sites to allow linearization and quantification usingabsorbance at 260 nm.

To allow for back calculation of strands in the eluted samples, QuARTSassays were performed on the 10 uL of eluents and serial dilutions ofthe digested plasmids.

Table 6D shows the obtained results for each of the tested markers.These results show that the methylation markers had high stranddifferences between positive and normal stool pool indicating thesemarkers are candidates for CRC detection in stool.

TABLE 6D Positives Normal Fold Pool Pool differences Methylation averageaverage (Positive/ Marker strands strands Normal) NDRG4 1,568 140 11.2BMP3 395 8 51.4 OPLAH 840 279 3.0 FLI1 1,715 167 10.2 PDGFD 843 67 12.6CHST2_7889 945 17 56.4 SFMBT2_895 837 5 152.3 SFMBT2_896 856 150 5.7SFMBT2_897 844 45 18.7 CHST2_7890 1,396 62 22.6 VAV3 367 21 17.9 DTX1751 105 7.2

Example 4 Exemplary Procedure for Screening for a Colorectal Cancerwithin a Human Subject

Contact a nucleic acid (e.g., genomic DNA, e.g., isolated from a bodyfluids such as a stool sample or colorectal tissue) obtained from ahuman subject with at least one reagent or series of reagents thatdistinguishes between methylated and non-methylated CpG dinucleotideswithin at least one marker DMR selected from:

-   -   FLI1, OPLAH, DTX1, MATK, and SFMBT2 region 2; (as recited in        Table 1);    -   BMP3, NDRG4, PDGFG, CHST2, and SFMBT2 (as recited in Table 2);    -   SFMBT2, LIFR, OPLAH, CRHR2, AGBL4, ZEB2, ZNF788, SFMBT2, ESR1,        ANKRD33B, CHST2 and FNDC1 (as recited in Table 3); and    -   NDRG4, BMP3, OPLAH, FLI1, PDGFD, CHST_7889, SFMBT2_895,        SFMBT2_896, SFMBT2_897, CHST2_7890, VAV3, and DTX1 (as recited        in Table 6).

Identifying the subject as having a colorectal cancer when themethylation state of the marker is different than a methylation state ofthe marker assayed in a subject that does not have a neoplasm.

Exemplary Procedure for Screening for a Colorectal Based Large Adenomawithin a Human Subject

Contact a nucleic acid (e.g., genomic DNA, e.g., isolated from a bodyfluids such as a stool sample or colorectal tissue) obtained from ahuman subject with at least one reagent or series of reagents thatdistinguishes between methylated and non-methylated CpG dinucleotideswithin at least one marker DMR selected from:

-   -   ADD2, AGBL4, AKAP12, ANKRD33B, ASCL1, C1orf70, CHST11, CHST15,        DTX1, ECEL1, EYA4, FLI1, FLJ43390, FLT3, GRASP, ITGA4, KCNQ2,        LOC100131199, LONFR2, MGAT3, OPLAH (145106742-145106921), OPLAH        (145106349-145106456), PDE8B, PDGFD, PKIA, POU3F1, QKI, RASSF2,        RSPO3, SDC2, SFMBT2 (7452746-7452779), SFMBT2 (7452029-7452452),        SFMBT2 (7450242-7450831), SOX5, VAV3 (108507609-108507674), VAV3        (108507074-108507498), and ZNF132 (as recited in Table 4).

Identifying the subject as having a colorectal based large adenoma whenthe methylation state of the marker is different than a methylationstate of the marker assayed in a subject that does not have a neoplasm.

Exemplary Procedure for Screening for Sessile Serrated Polyps (SSP)within a Human Subject

Contact a nucleic acid (e.g., genomic DNA, e.g., isolated from a bodyfluids such as a stool sample or colorectal tissue) obtained from ahuman subject with at least one reagent or series of reagents thatdistinguishes between methylated and non-methylated CpG dinucleotideswithin at least one marker DMR selected from:

-   -   CAMK4, FGF9, GJC1, GPX7, GRIN2A, IGF2BP3,        MAX.chr19.55963254-55963329, MAX.chr2.127783352-127783403,        MAX.chr4.186049639-186049660, NRG1, NTNG1, PIK3CD, PTENP1,        RAB31, RNF220, SLC30A10, and ZNF853 (as recited in Table 5).

Identifying the subject as having a sessile serrated polyps when themethylation state of the marker is different than a methylation state ofthe marker assayed in a subject that does not have a neoplasm.

Exemplary Procedure for Screening for a Colorectal Cancer within a HumanSubject Having Inflammatory Bowel Disease

Contact a nucleic acid (e.g., genomic DNA, e.g., isolated from a bodyfluids such as a stool sample or colorectal tissue) obtained from ahuman subject having inflammatory bowel disease with at least onereagent or series of reagents that distinguishes between methylated andnon-methylated CpG dinucleotides within at least one marker DMR selectedfrom:

-   -   BMP3, NDRG4, PDGFG, CHST2, and SFMBT2 (as recited in Table 2).

Identifying the subject as having a colorectal cancer when themethylation state of the marker is different than a methylation state ofthe marker assayed in a subject that does not have a neoplasm.

All publications and patents mentioned in the above specification areherein incorporated by reference in their entirety for all purposes.Various modifications and variations of the described compositions,methods, and uses of the technology will be apparent to those skilled inthe art without departing from the scope and spirit of the technology asdescribed. Although the technology has been described in connection withspecific exemplary embodiments, it should be understood that theinvention as claimed should not be unduly limited to such specificembodiments. Indeed, various modifications of the described modes forcarrying out the invention that are obvious to those skilled inpharmacology, biochemistry, medical science, or related fields areintended to be within the scope of the following claims.

1-106. (canceled)
 107. A method of screening for colorectal neoplasm ina sample obtained from a subject, the method comprising: a) assaying amethylation state of a marker in a sample obtained from a subject; andb) identifying the subject as having colorectal neoplasm when themethylation state of the marker is different than a methylation state ofthe marker assayed in a subject that does not have colorectal neoplasm,wherein the marker comprises a base in a differentially methylatedregion (DMR) selected from ANKRD33B, LRRC4, QKI, PPP2R5C, and ZNF568.108. The method of claim 107 wherein the sample comprises colorectaltissue.
 109. The method of claim 107, wherein the sample comprises astool sample, a blood sample, and/or a blood fraction sample.
 110. Themethod of claim 107, wherein the methylation state of the markercomprises an increased methylation of the marker relative to a normalmethylation state of the marker.
 111. The method of claim 107, whereinthe methylation state of the marker comprises a different pattern ofmethylation of the marker relative to a normal methylation state of themarker.
 112. The method of claim 107, wherein the assaying comprises useof a methylation specific oligonucleotide.
 113. The method of claim 107,wherein the assaying utilizes methylation specific polymerase chainreaction.
 114. The method of claim 107, wherein the assaying utilizesnucleic acid sequencing.
 115. The method of claim 107, wherein theassaying utilizes mass spectrometry.
 116. The method of claim 107,wherein the assaying utilizes methylation specific nuclease.
 117. Themethod of claim 107, wherein the assaying comprises using methylationspecific polymerase chain reaction, nucleic acid sequencing, massspectrometry, methylation specific nuclease, mass-based separation, ortarget capture.
 118. A method for characterizing a biological samplecomprising: (a) measuring a methylation level of a CpG site for one ormore genes selected from ANKRD33B, LRRC4, QKI, PPP2R5C, and ZNF568 in abiological sample of a human individual through treating genomic DNA inthe biological sample with bisulfite; amplifying the bisulfite-treatedgenomic DNA using a set of primers for the selected one or more genes;and determining the methylation level of the CpG site bymethylation-specific PCR, quantitative methylation-specific PCR,methylation-sensitive DNA restriction enzyme analysis, quantitativebisulfite pyrosequencing, or bisulfite genomic sequencing PCR; (b)comparing the methylation level to a methylation level of acorresponding set of genes in control samples without colorectalneoplasm; and (c) determining that the individual has colorectalneoplasm when the methylation level measured in the one or more genes ishigher than the methylation level measured in the respective controlsamples.
 119. The method of claim 118, wherein the biological sample isa stool sample, a tissue sample, a blood sample, or a urine sample. 120.The method of claim 118, wherein the biological sample is a colorectaltissue sample.
 121. The method of claim 118, wherein said CpG site ispresent in a coding region or a regulatory region.
 122. The method ofclaim 118, wherein said measuring the methylation level a CpG site fortwo or more genes comprises a determination selected from the groupconsisting of determining the methylation score of said CpG site anddetermining the methylation frequency of said CpG site.
 123. The methodof claim 118, wherein the one or more genes at least includes QKI,wherein the set of primers is SEQ ID Nos: 32 and
 33. 124. The method ofclaim 118, wherein the one or more genes at least includes PPP2R5C,wherein the set of primers is SEQ ID Nos: 18 and 19.